Bibliography.bib

@misc{lecun1994mnist,
  title={The {MNIST} database of handwritten digits},
  author={Yann LeCun and Corinna Cortes and Christopher J.~C. Burges},
  howpublished={\url{http://yann.lecun.com/exdb/mnist/}, 1994},
  year={1996}
}

@inproceedings{sabatelli2021transferability,
  title={On The Transferability of Deep-Q Networks},
  author={Sabatelli, Matthia and Geurts, Pierre},
  booktitle={Deep Reinforcement Learning Workshop of the 35th Conference on Neural Information Processing Systems},
  year={2021}
}


@misc{dogoimage,
  howpublished = "\url{https://www.aspexit.com/neural-network-lets-try-to-demystify-all-this-a-little-bit-3-application-to-images/}"
}


@inproceedings{dai2008self,
  title={Self-taught clustering},
  author={Dai, Wenyuan and Yang, Qiang and Xue, Gui-Rong and Yu, Yong},
  booktitle={Proceedings of the 25th international conference on Machine learning},
  pages={200--207},
  year={2008}
}

@article{zhao2011reinforcement,
  title={Reinforcement learning strategies for clinical trials in nonsmall cell lung cancer},
  author={Zhao, Yufan and Zeng, Donglin and Socinski, Mark A and Kosorok, Michael R},
  journal={Biometrics},
  volume={67},
  number={4},
  pages={1422--1433},
  year={2011},
  publisher={Wiley Online Library}
}

@article{zhu2016robust,
  title={Robust joint graph sparse coding for unsupervised spectral feature selection},
  author={Zhu, Xiaofeng and Li, Xuelong and Zhang, Shichao and Ju, Chunhua and Wu, Xindong},
  journal={IEEE transactions on neural networks and learning systems},
  volume={28},
  number={6},
  pages={1263--1275},
  year={2016},
  publisher={IEEE}
}

@article{liu2021efficient,
  title={Efficient Training of Visual Transformers with Small Datasets},
  author={Liu, Yahui and Sangineto, Enver and Bi, Wei and Sebe, Nicu and Lepri, Bruno and Nadai, Marco},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

@article{silver2017mastering,
  title={Mastering the game of go without human knowledge},
  author={Silver, David and Schrittwieser, Julian and Simonyan, Karen and Antonoglou, Ioannis and Huang, Aja and Guez, Arthur and Hubert, Thomas and Baker, Lucas and Lai, Matthew and Bolton, Adrian and others},
  journal={nature},
  volume={550},
  number={7676},
  pages={354--359},
  year={2017},
  publisher={Nature Publishing Group}
}

@article{yosinski2014transferable,
  title={How transferable are features in deep neural networks?},
  author={Yosinski, Jason and Clune, Jeff and Bengio, Yoshua and Lipson, Hod},
  journal={arXiv preprint arXiv:1411.1792},
  year={2014}
}

@article{zhu2020transfer,
  title={Transfer Learning in Deep Reinforcement Learning: A Survey},
  author={Zhu, Zhuangdi and Lin, Kaixiang and Zhou, Jiayu},
  journal={arXiv preprint arXiv:2009.07888},
  year={2020}
}

@inproceedings{tirinzoni2018transfer,
  title={Transfer of value functions via variational methods},
  author={Tirinzoni, Andrea and Sanchez, Rafael Rodriguez and Restelli, Marcello},
  booktitle={Advances in Neural Information Processing Systems},
  pages={6179--6189},
  year={2018}
}

@article{ha2018world,
  title={World models},
  author={Ha, David and Schmidhuber, J{\"u}rgen},
  journal={arXiv preprint arXiv:1803.10122},
  year={2018}
}

@inproceedings{zhu2017target,
  title={Target-driven visual navigation in indoor scenes using deep reinforcement learning},
  author={Zhu, Yuke and Mottaghi, Roozbeh and Kolve, Eric and Lim, Joseph J and Gupta, Abhinav and Fei-Fei, Li and Farhadi, Ali},
  booktitle={2017 IEEE international conference on robotics and automation (ICRA)},
  pages={3357--3364},
  year={2017},
  organization={IEEE}
}


@article{chen2021improving,
  title={Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings},
  author={Chen, Lili and Lee, Kimin and Srinivas, Aravind and Abbeel, Pieter},
  journal={arXiv preprint arXiv:2103.02886},
  year={2021}
}

@article{landolfi2019model,
  title={A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning},
  author={Landolfi, Nicholas C and Thomas, Garrett and Ma, Tengyu},
  journal={arXiv preprint arXiv:1907.04964},
  year={2019}
}


@article{rusu2016progressive,
  title={Progressive neural networks},
  author={Rusu, Andrei A and Rabinowitz, Neil C and Desjardins, Guillaume and Soyer, Hubert and Kirkpatrick, James and Kavukcuoglu, Koray and Pascanu, Razvan and Hadsell, Raia},
  journal={arXiv preprint arXiv:1606.04671},
  year={2016}
}


@article{vandaele2021deep,
  title={Deep learning for automated river-level monitoring through river-camera images: an approach based on water segmentation and transfer learning},
  author={Vandaele, Remy and Dance, Sarah L and Ojha, Varun},
  journal={Hydrology and Earth System Sciences},
  volume={25},
  number={8},
  pages={4435--4453},
  year={2021},
  publisher={Copernicus GmbH}
}


@inproceedings{hafner2019learning,
  title={Learning latent dynamics for planning from pixels},
  author={Hafner, Danijar and Lillicrap, Timothy and Fischer, Ian and Villegas, Ruben and Ha, David and Lee, Honglak and Davidson, James},
  booktitle={International Conference on Machine Learning},
  pages={2555--2565},
  year={2019},
  organization={PMLR}
}

@article{hafner2019dream,
  title={Dream to control: Learning behaviors by latent imagination},
  author={Hafner, Danijar and Lillicrap, Timothy and Ba, Jimmy and Norouzi, Mohammad},
  journal={arXiv preprint arXiv:1912.01603},
  year={2019}
}

@article{hafner2020mastering,
  title={Mastering atari with discrete world models},
  author={Hafner, Danijar and Lillicrap, Timothy and Norouzi, Mohammad and Ba, Jimmy},
  journal={arXiv preprint arXiv:2010.02193},
  year={2020}
}



@inproceedings{kim2019deepmellow,
  title={Deepmellow: removing the need for a target network in deep Q-learning},
  author={Kim, Seungchan and Asadi, Kavosh and Littman, Michael and Konidaris, George},
  booktitle={Proceedings of the Twenty Eighth International Joint Conference on Artificial Intelligence},
  year={2019}
}

@article{piche2021beyond,
  title={Beyond Target Networks: Improving Deep $ Q $-learning with Functional Regularization},
  author={Pich{\'e}, Alexandre and Marino, Joseph and Marconi, Gian Maria and Pal, Christopher and Khan, Mohammad Emtiyaz},
  journal={arXiv preprint arXiv:2106.02613},
  year={2021}
}



@inproceedings{jin2011transferring,
  title={Transferring topical knowledge from auxiliary long texts for short text clustering},
  author={Jin, Ou and Liu, Nathan N and Zhao, Kai and Yu, Yong and Yang, Qiang},
  booktitle={Proceedings of the 20th ACM international conference on Information and knowledge management},
  pages={775--784},
  year={2011}
}

@inproceedings{wang2008transferred,
  title={Transferred dimensionality reduction},
  author={Wang, Zheng and Song, Yangqiu and Zhang, Changshui},
  booktitle={Joint European conference on machine learning and knowledge discovery in databases},
  pages={550--565},
  year={2008},
  organization={Springer}
}

@article{qian2015cluster,
  title={Cluster prototypes and fuzzy memberships jointly leveraged cross-domain maximum entropy clustering},
  author={Qian, Pengjiang and Jiang, Yizhang and Deng, Zhaohong and Hu, Lingzhi and Sun, Shouwei and Wang, Shitong and Muzic, Raymond F},
  journal={IEEE transactions on cybernetics},
  volume={46},
  number={1},
  pages={181--193},
  year={2015},
  publisher={IEEE}
}

@article{zhu2013self,
  title={Self-taught dimensionality reduction on the high-dimensional small-sized data},
  author={Zhu, Xiaofeng and Huang, Zi and Yang, Yang and Shen, Heng Tao and Xu, Changsheng and Luo, Jiebo},
  journal={Pattern Recognition},
  volume={46},
  number={1},
  pages={215--229},
  year={2013},
  publisher={Elsevier}
}

@misc{raghakotkerasvis,
  title={keras-vis},
  author={Kotikalapudi, Raghavendra and contributors},
  year={2017},
  publisher={GitHub},
  howpublished={\url{https://github.com/raghakot/keras-vis}},
}

@article{xiao2017fashion,
  title={Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms},
  author={Xiao, Han and Rasul, Kashif and Vollgraf, Roland},
  journal={arXiv preprint arXiv:1708.07747},
  year={2017}
}


@article{clanuwat2018deep,
  title={Deep learning for classical japanese literature},
  author={Clanuwat, Tarin and Bober-Irizar, Mikel and Kitamoto, Asanobu and Lamb, Alex and Yamamoto, Kazuaki and Ha, David},
  journal={arXiv preprint arXiv:1812.01718},
  year={2018}
}

@inproceedings{langley2006transfer,
  title={Transfer of knowledge in cognitive systems},
  author={Langley, Pat},
  booktitle={Talk, workshop on Structural Knowledge Transfer for Machine Learning at the Twenty-Third International Conference on Machine Learning},
  year={2006}
}

@inproceedings{arnold2007comparative,
  title={A comparative study of methods for transductive transfer learning},
  author={Arnold, Andrew and Nallapati, Ramesh and Cohen, William W},
  booktitle={Seventh IEEE international conference on data mining workshops (ICDMW 2007)},
  pages={77--82},
  year={2007},
  organization={IEEE}
}

@article{pan2009survey,
  title={A survey on transfer learning},
  author={Pan, Sinno Jialin and Yang, Qiang},
  journal={IEEE Transactions on knowledge and data engineering},
  volume={22},
  number={10},
  pages={1345--1359},
  year={2009},
  publisher={IEEE}
}

@article{zhuang2020comprehensive,
  title={A comprehensive survey on transfer learning},
  author={Zhuang, Fuzhen and Qi, Zhiyuan and Duan, Keyu and Xi, Dongbo and Zhu, Yongchun and Zhu, Hengshu and Xiong, Hui and He, Qing},
  journal={Proceedings of the IEEE},
  volume={109},
  number={1},
  pages={43--76},
  year={2020},
  publisher={IEEE}
}

@inproceedings{taylor2008transferring,
  title={Transferring instances for model-based reinforcement learning},
  author={Taylor, Matthew E and Jong, Nicholas K and Stone, Peter},
  booktitle={Joint European conference on machine learning and knowledge discovery in databases},
  pages={488--505},
  year={2008},
  organization={Springer}
}

@inproceedings{lazaric2008transfer,
  title={Transfer of samples in batch reinforcement learning},
  author={Lazaric, Alessandro and Restelli, Marcello and Bonarini, Andrea},
  booktitle={Proceedings of the 25th international conference on Machine learning},
  pages={544--551},
  year={2008}
}

@article{taylor2009transfer,
  title={Transfer learning for reinforcement learning domains: A survey.},
  author={Taylor, Matthew E and Stone, Peter},
  journal={Journal of Machine Learning Research},
  volume={10},
  number={7},
  year={2009}
}

@inproceedings{sharif2014cnn,
  title={CNN features off-the-shelf: an astounding baseline for recognition},
  author={Sharif Razavian, Ali and Azizpour, Hossein and Sullivan, Josephine and Carlsson, Stefan},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition workshops},
  pages={806--813},
  year={2014}
}

@article{wang2014action,
  title={Action recognition and detection by combining motion and appearance features},
  author={Wang, Limin and Qiao, Yu and Tang, Xiaoou},
  journal={THUMOS14 Action Recognition Challenge},
  volume={1},
  number={2},
  pages={2},
  year={2014},
  publisher={Citeseer}
}

@article{zhou2014learning,
  title={Learning deep features for scene recognition using places database},
  author={Zhou, Bolei and Lapedriza, Agata and Xiao, Jianxiong and Torralba, Antonio and Oliva, Aude},
  year={2014},
  publisher={Neural Information Processing Systems Foundation}
}

@inproceedings{van2015off,
  title={Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans},
  author={Van Ginneken, Bram and Setio, Arnaud AA and Jacobs, Colin and Ciompi, Francesco},
  booktitle={2015 IEEE 12th International symposium on biomedical imaging (ISBI)},
  pages={286--289},
  year={2015},
  organization={IEEE}
}

@inproceedings{sharma2015adapting,
  title={Adapting off-the-shelf CNNs for word spotting \& recognition},
  author={Sharma, Arjun and others},
  booktitle={2015 13th International Conference on Document Analysis and Recognition (ICDAR)},
  pages={986--990},
  year={2015},
  organization={IEEE}
}

@article{nguyen2017iris,
  title={Iris recognition with off-the-shelf CNN features: A deep learning perspective},
  author={Nguyen, Kien and Fookes, Clinton and Ross, Arun and Sridharan, Sridha},
  journal={IEEE Access},
  volume={6},
  pages={18848--18855},
  year={2017},
  publisher={IEEE}
}

@inproceedings{laroche2017transfer,
  title={Transfer reinforcement learning with shared dynamics},
  author={Laroche, Romain and Barlier, Merwan},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={31},
  number={1},
  year={2017}
}

@article{lowe2004distinctive,
  title={Distinctive image features from scale-invariant keypoints},
  author={Lowe, David G},
  journal={International journal of computer vision},
  volume={60},
  number={2},
  pages={91--110},
  year={2004},
  publisher={Springer}
}


@inproceedings{dalal2005histograms,
  title={Histograms of oriented gradients for human detection},
  author={Dalal, Navneet and Triggs, Bill},
  booktitle={2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05)},
  volume={1},
  pages={886--893},
  year={2005},
  organization={Ieee}
}

@inproceedings{kornblith2019better,
  title={Do better imagenet models transfer better?},
  author={Kornblith, Simon and Shlens, Jonathon and Le, Quoc V},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={2661--2671},
  year={2019}
}

@article{mikolov2013efficient,
  title={Efficient estimation of word representations in vector space},
  author={Mikolov, Tomas and Chen, Kai and Corrado, Greg and Dean, Jeffrey},
  journal={arXiv preprint arXiv:1301.3781},
  year={2013}
}

@article{brown2020language,
  title={Language models are few-shot learners},
  author={Brown, Tom B and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and others},
  journal={arXiv preprint arXiv:2005.14165},
  year={2020}
}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{rosset2020knowledge,
  title={Knowledge-Aware Language Model Pretraining},
  author={Rosset, Corby and Xiong, Chenyan and Phan, Minh and Song, Xia and Bennett, Paul and Tiwary, Saurabh},
  journal={arXiv preprint arXiv:2007.00655},
  year={2020}
}

@article{huh2016makes,
  title={What makes ImageNet good for transfer learning?},
  author={Huh, Minyoung and Agrawal, Pulkit and Efros, Alexei A},
  journal={arXiv preprint arXiv:1608.08614},
  year={2016}
}

@article{farebrother2018generalization,
  title={Generalization and regularization in DQN},
  author={Farebrother, Jesse and Machado, Marlos C and Bowling, Michael},
  journal={arXiv preprint arXiv:1810.00123},
  year={2018}
}

@article{parisotto2015actor,
  title={Actor-mimic: Deep multitask and transfer reinforcement learning},
  author={Parisotto, Emilio and Ba, Jimmy Lei and Salakhutdinov, Ruslan},
  journal={arXiv preprint arXiv:1511.06342},
  year={2015}
}


@article{tyo2020transferable,
  title={How transferable are the representations learned by deep q agents?},
  author={Tyo, Jacob and Lipton, Zachary},
  journal={arXiv preprint arXiv:2002.10021},
  year={2020}
}

@article{mensink2021factors,
  title={Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types},
  author={Mensink, Thomas and Uijlings, Jasper and Kuznetsova, Alina and Gygli, Michael and Ferrari, Vittorio},
  journal={arXiv preprint arXiv:2103.13318},
  year={2021}
}

@inproceedings{tirinzoni2018importance,
  title={Importance weighted transfer of samples in reinforcement learning},
  author={Tirinzoni, Andrea and Sessa, Andrea and Pirotta, Matteo and Restelli, Marcello},
  booktitle={International Conference on Machine Learning},
  pages={4936--4945},
  year={2018},
  organization={PMLR}
}

@article{sasso2021fractional,
  title={Fractional Transfer Learning for Deep Model-Based Reinforcement Learning},
  author={Sasso, Remo and Sabatelli, Matthia and Wiering, Marco A},
  journal={arXiv preprint arXiv:2108.06526},
  year={2021}
}

@incollection{lazaric2012transfer,
  title={Transfer in reinforcement learning: a framework and a survey},
  author={Lazaric, Alessandro},
  booktitle={Reinforcement Learning},
  pages={143--173},
  year={2012},
  publisher={Springer}
}

@article{breiman2001random,
  title={Random forests},
  author={Breiman, Leo},
  journal={Machine learning},
  volume={45},
  number={1},
  pages={5--32},
  year={2001},
  publisher={Springer}
}

@inproceedings{sabatelli2018deep,
  title={Deep transfer learning for art classification problems},
  author={Sabatelli, Matthia and Kestemont, Mike and Daelemans, Walter and Geurts, Pierre},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
  pages={631--646},
  year={2018}
}

@inproceedings{sabatelli2020transferability,
  title={On the transferability of winning tickets in non-natural image datasets},
  author={Sabatelli, Matthia and Kestemont, Mike and Geurts, Pierre},
  booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)},
  pages={59--69},  
  year={2021},
  publisher={SciTePress}
}

@article{hessel2019inductive,
  title={On inductive biases in deep reinforcement learning},
  author={Hessel, Matteo and van Hasselt, Hado and Modayil, Joseph and Silver, David},
  journal={arXiv preprint arXiv:1907.02908},
  year={2019}
}

@article{tseng2017deep,
  title={Deep reinforcement learning for automated radiation adaptation in lung cancer},
  author={Tseng, Huan-Hsin and Luo, Yi and Cui, Sunan and Chien, Jen-Tzung and Ten Haken, Randall K and Naqa, Issam El},
  journal={Medical physics},
  volume={44},
  number={12},
  pages={6690--6705},
  year={2017},
  publisher={Wiley Online Library}
}

@article{kalashnikov2018qt,
  title={Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation},
  author={Kalashnikov, Dmitry and Irpan, Alex and Pastor, Peter and Ibarz, Julian and Herzog, Alexander and Jang, Eric and Quillen, Deirdre and Holly, Ethan and Kalakrishnan, Mrinal and Vanhoucke, Vincent and others},
  journal={arXiv preprint arXiv:1806.10293},
  year={2018}
}

@article{he2015deep,
  title={Deep reinforcement learning with a natural language action space},
  author={He, Ji and Chen, Jianshu and He, Xiaodong and Gao, Jianfeng and Li, Lihong and Deng, Li and Ostendorf, Mari},
  journal={arXiv preprint arXiv:1511.04636},
  year={2015}
}

@article{narasimhan2015language,
  title={Language understanding for text-based games using deep reinforcement learning},
  author={Narasimhan, Karthik and Kulkarni, Tejas and Barzilay, Regina},
  journal={arXiv preprint arXiv:1506.08941},
  year={2015}
}

@inproceedings{sutton1999policy,
  title={Policy gradient methods for reinforcement learning with function approximation.},
  author={Sutton, Richard S and McAllester, David A and Singh, Satinder P and Mansour, Yishay and others},
  booktitle={NIPs},
  volume={99},
  pages={1057--1063},
  year={1999},
  organization={Citeseer}
}

@article{williams1992simple,
  title={Simple statistical gradient-following algorithms for connectionist reinforcement learning},
  author={Williams, Ronald J},
  journal={Machine learning},
  volume={8},
  number={3-4},
  pages={229--256},
  year={1992},
  publisher={Springer}
}



@inproceedings{raghu2017continuous,
  title={Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach},
  author={Raghu, Aniruddh and Komorowski, Matthieu and Celi, Leo Anthony and Szolovits, Peter and Ghassemi, Marzyeh},
  booktitle={Machine Learning for Healthcare Conference},
  pages={147--163},
  year={2017},
  organization={PMLR}
}

@article{liu2017learning,
  title={Learning to schedule control fragments for physics-based characters using deep q-learning},
  author={Liu, Libin and Hodgins, Jessica},
  journal={ACM Transactions on Graphics (TOG)},
  volume={36},
  number={3},
  pages={1--14},
  year={2017},
  publisher={ACM New York, NY, USA}
}

@article{sajedian2020design,
  title={Design of high transmission color filters for solar cells directed by deep Q-learning},
  author={Sajedian, Iman and Lee, Heon and Rho, Junsuk},
  journal={Solar Energy},
  volume={195},
  pages={670--676},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{morcos2019one,
  title={One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers},
  author={Morcos, Ari and Yu, Haonan and Paganini, Michela and Tian, Yuandong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={4933--4943},
  year={2019}
}

@article{yu2019playing,
  title={Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP},
  author={Yu, Haonan and Edunov, Sergey and Tian, Yuandong and Morcos, Ari S},
  journal={arXiv preprint arXiv:1906.02768},
  year={2019}
}

@inproceedings{zhou2019deconstructing,
  title={Deconstructing lottery tickets: Zeros, signs, and the supermask},
  author={Zhou, Hattie and Lan, Janice and Liu, Rosanne and Yosinski, Jason},
  booktitle={Advances in Neural Information Processing Systems},
  pages={3592--3602},
  year={2019}
}

@article{mehta2019sparse,
  title={Sparse Transfer Learning via Winning Lottery Tickets},
  author={Mehta, Rahul},
  journal={arXiv preprint arXiv:1905.07785},
  year={2019}
}
@article{frankle2018lottery,
  title={The lottery ticket hypothesis: Finding sparse, trainable neural networks},
  author={Frankle, Jonathan and Carbin, Michael},
  journal={arXiv preprint arXiv:1803.03635},
  year={2018}
}

@article{mehta2008transfer,
  title={Transfer in variable-reward hierarchical reinforcement learning},
  author={Mehta, Neville and Natarajan, Sriraam and Tadepalli, Prasad and Fern, Alan},
  journal={Machine Learning},
  volume={73},
  number={3},
  pages={289},
  year={2008},
  publisher={Springer}
}

@inproceedings{barreto2017successor,
  title={Successor features for transfer in reinforcement learning},
  author={Barreto, Andr{\'e} and Dabney, Will and Munos, R{\'e}mi and Hunt, Jonathan J and Schaul, Tom and van Hasselt, Hado P and Silver, David},
  booktitle={Advances in neural information processing systems},
  pages={4055--4065},
  year={2017}
}

@inproceedings{han2015learning,
  title={Learning both weights and connections for efficient neural network},
  author={Han, Song and Pool, Jeff and Tran, John and Dally, William},
  booktitle={Advances in neural information processing systems},
  pages={1135--1143},
  year={2015}
}

@article{frankle2019linear,
  title={Linear mode connectivity and the lottery ticket hypothesis},
  author={Frankle, Jonathan and Dziugaite, Gintare Karolina and Roy, Daniel M and Carbin, Michael},
  journal={arXiv preprint arXiv:1912.05671},
  year={2019}
}


@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

@article{han2015deep,
  title={Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding},
  author={Han, Song and Mao, Huizi and Dally, William J},
  journal={arXiv preprint arXiv:1510.00149},
  year={2015}
}

@inproceedings{zhuang2018discrimination,
  title={Discrimination-aware channel pruning for deep neural networks},
  author={Zhuang, Zhuangwei and Tan, Mingkui and Zhuang, Bohan and Liu, Jing and Guo, Yong and Wu, Qingyao and Huang, Junzhou and Zhu, Jinhui},
  booktitle={Advances in Neural Information Processing Systems},
  pages={875--886},
  year={2018}
}

@article{franklestabilizing,
  title={Stabilizing the Lottery Ticket Hypothesis},
  author={Frankle, Jonathan and Dziugaite, G Karolina and Roy, DM and Carbin, M},
  journal={arXiv preprint arXiv:1903.01611},
  year = {2019}
}

@article{molchanov2016pruning,
  title={Pruning convolutional neural networks for resource efficient inference},
  author={Molchanov, Pavlo and Tyree, Stephen and Karras, Tero and Aila, Timo and Kautz, Jan},
  journal={arXiv preprint arXiv:1611.06440},
  year={2016}
}

@inproceedings{hassibi1993optimal,
  title={Optimal brain surgeon and general network pruning},
  author={Hassibi, Babak and Stork, David G and Wolff, Gregory J},
  booktitle={IEEE international conference on neural networks},
  pages={293--299},
  year={1993},
  organization={IEEE}
}

@inproceedings{lecun1990optimal,
  title={Optimal brain damage},
  author={LeCun, Yann and Denker, John S and Solla, Sara A},
  booktitle={Advances in neural information processing systems},
  pages={598--605},
  year={1990}
}

@article{maree2016collaborative,
  title={Collaborative analysis of multi-gigapixel imaging data using Cytomine},
  author={Mar{\'e}e, Rapha{\"e}l and Rollus, Lo{\"\i}c and St{\'e}vens, Benjamin and Hoyoux, Renaud and Louppe, Gilles and Vandaele, R{\'e}my and Begon, Jean-Michel and Kainz, Philipp and Geurts, Pierre and Wehenkel, Louis},
  journal={Bioinformatics},
  volume={32},
  number={9},
  pages={1395--1401},
  year={2016},
  publisher={Oxford University Press}
}

@inproceedings{gonthier2018weakly,
  title={Weakly supervised object detection in artworks},
  author={Gonthier, Nicolas and Gousseau, Yann and Ladjal, Said and Bonfait, Olivier},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
  pages={0--0},
  year={2018}
}

@inproceedings{redmon2017yolo9000,
  title={YOLO9000: better, faster, stronger},
  author={Redmon, Joseph and Farhadi, Ali},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={7263--7271},
  year={2017}
}

@inproceedings{selvaraju2017grad,
  title={Grad-cam: Visual explanations from deep networks via gradient-based localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={618--626},
  year={2017}
}

@article{lecun1998gradient,
  title={Gradient-based learning applied to document recognition},
  author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
  journal={Proceedings of the IEEE},
  volume={86},
  number={11},
  pages={2278--2324},
  year={1998},
  publisher={Ieee}
}

@inproceedings{chattopadhay2018grad,
  title={Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks},
  author={Chattopadhay, Aditya and Sarkar, Anirban and Howlader, Prantik and Balasubramanian, Vineeth N},
  booktitle={2018 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  pages={839--847},
  year={2018},
  organization={IEEE}
}

@article{linnainmaa1970representation,
  title={The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors},
  author={Linnainmaa, Seppo},
  journal={Master's Thesis (in Finnish), Univ. Helsinki},
  pages={6--7},
  year={1970}
}

@article{arun2020assessing,
  title={Assessing the (un) trustworthiness of saliency maps for localizing abnormalities in medical imaging},
  author={Arun, Nishanth and Gaw, Nathan and Singh, Praveer and Chang, Ken and Aggarwal, Mehak and Chen, Bryan and Hoebel, Katharina and Gupta, Sharut and Patel, Jay and Gidwani, Mishka and others},
  journal={arXiv preprint arXiv:2008.02766},
  year={2020}
}

@article{saporta2021deep,
  title={Deep learning saliency maps do not accurately highlight diagnostically relevant regions for medical image interpretation},
  author={Saporta, Adriel and Gui, Xiaotong and Agrawal, Ashwin and Pareek, Anuj and Truong, Steven QH and Nguyen, Chanh DT and Ngo, Van-Doan and Seekins, Jayne and Blankenberg, Francis G and Ng, Andrew and others},
  journal={medRxiv},
  year={2021},
  publisher={Cold Spring Harbor Laboratory Press}
}

@article{simonyan2013deep,
  title={Deep inside convolutional networks: Visualising image classification models and saliency maps},
  author={Simonyan, Karen and Vedaldi, Andrea and Zisserman, Andrew},
  journal={arXiv preprint arXiv:1312.6034},
  year={2013}
}

@inproceedings{alqaraawi2020evaluating,
  title={Evaluating saliency map explanations for convolutional neural networks: a user study},
  author={Alqaraawi, Ahmed and Schuessler, Martin and Wei{\ss}, Philipp and Costanza, Enrico and Berthouze, Nadia},
  booktitle={Proceedings of the 25th International Conference on Intelligent User Interfaces},
  pages={275--285},
  year={2020}
}

@article{redmon2018yolov3,
  title={Yolov3: An incremental improvement},
  author={Redmon, Joseph and Farhadi, Ali},
  journal={arXiv preprint arXiv:1804.02767},
  year={2018}
}

@article{paganini2020bespoke,
  title={Bespoke vs. Pr{\^{e}}t-{\`{a}}-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding},
  author={Paganini, Michela and Forde, Jessica Zosa},
  journal={arXiv preprint arXiv:2007.04091},
  year={2020}
}

@inproceedings{nesterov1983method,
  title={A method for solving the convex programming problem with convergence rate O (1/k\^{} 2)},
  author={Nesterov, Yurii E},
  booktitle={Dokl. akad. nauk Sssr},
  volume={269},
  pages={543--547},
  year={1983}
}

@inproceedings{ronneberger2015u,
  title={U-net: Convolutional networks for biomedical image segmentation},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={234--241},
  year={2015},
  organization={Springer}
}

@inproceedings{lin2014microsoft,
  title={Microsoft coco: Common objects in context},
  author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
  booktitle={European conference on computer vision},
  pages={740--755},
  year={2014},
  organization={Springer}
}

@inproceedings{vapnik1992principles,
  title={Principles of risk minimization for learning theory},
  author={Vapnik, Vladimir},
  booktitle={Advances in neural information processing systems},
  pages={831--838},
  year={1992}
}

@article{gohil2019one,
  title={One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers},
  author={Gohil, Varun and Narayanan, S Deepak and Jain, Atishay},
  journal={ReScience-C},
  year={2020}
}

@article{russakovsky2015imagenet,
  title={Imagenet large scale visual recognition challenge},
  author={Russakovsky, Olga and Deng, Jia and Su, Hao and Krause, Jonathan and Satheesh, Sanjeev and Ma, Sean and Huang, Zhiheng and Karpathy, Andrej and Khosla, Aditya and Bernstein, Michael and others},
  journal={International journal of computer vision},
  volume={115},
  number={3},
  pages={211--252},
  year={2015},
  publisher={Springer}
}

@article{baydin2018automatic,
  title={Automatic differentiation in machine learning: a survey},
  author={Baydin, Atilim Gunes and Pearlmutter, Barak A and Radul, Alexey Andreyevich and Siskind, Jeffrey Mark},
  journal={Journal of machine learning research},
  volume={18},
  year={2018},
  publisher={Journal of Machine Learning Research}
}

@phdthesis{geurts2002contributions,
  title={Contributions to decision tree induction: bias/variance tradeoff and time series classification},
  author={Geurts, Pierre},
  year={2002},
  school={ULi{\`e}ge-University of Li{\`e}ge}
}

@book{friedman2001elements,
  title={The elements of statistical learning},
  author={Friedman, Jerome and Hastie, Trevor and Tibshirani, Robert and others},
  volume={1},
  number={10},
  year={2001},
  publisher={Springer series in statistics New York}
}

@article{louppe2014understanding,
  title={Understanding random forests: From theory to practice},
  author={Louppe, Gilles},
  journal={arXiv preprint arXiv:1407.7502},
  year={2014}
}

@article{rumelhart1986learning,
  title={Learning representations by back-propagating errors},
  author={Rumelhart, David E and Hinton, Geoffrey E and Williams, Ronald J},
  journal={nature},
  volume={323},
  number={6088},
  pages={533--536},
  year={1986},
  publisher={Nature Publishing Group}
}

@article{everingham2010pascal,
  title={The pascal visual object classes (voc) challenge},
  author={Everingham, Mark and Van Gool, Luc and Williams, Christopher KI and Winn, John and Zisserman, Andrew},
  journal={International journal of computer vision},
  volume={88},
  number={2},
  pages={303--338},
  year={2010},
  publisher={Springer}
}

@article{schmidt2020descending,
  title={Descending through a Crowded Valley--Benchmarking Deep Learning Optimizers},
  author={Schmidt, Robin M and Schneider, Frank and Hennig, Philipp},
  journal={arXiv preprint arXiv:2007.01547},
  year={2020}
}

@article{ruder2016overview,
  title={An overview of gradient descent optimization algorithms},
  author={Ruder, Sebastian},
  journal={arXiv preprint arXiv:1609.04747},
  year={2016}
}

@article{sun2019learning,
  title={Learning Sparse Sharing Architectures for Multiple Tasks},
  author={Sun, Tianxiang and Shao, Yunfan and Li, Xiaonan and Liu, Pengfei and Yan, Hang and Qiu, Xipeng and Huang, Xuanjing},
  journal={arXiv preprint arXiv:1911.05034},
  year={2019}
}

@article{bottou201113,
  title={13 the tradeoffs of large-scale learning},
  author={Bottou, L{\'e}on and Bousquet, Olivier},
  journal={Optimization for machine learning},
  pages={351},
  year={2011},
  publisher={MIT Press}
}

@inproceedings{tan2019review,
  title={Review of second-order optimization techniques in artificial neural networks backpropagation},
  author={Tan, Hong Hui and Lim, King Hann},
  booktitle={IOP Conference Series: Materials Science and Engineering},
  volume={495},
  number={1},
  pages={012003},
  year={2019},
  organization={IOP Publishing}
}

@article{desai2019evaluating,
  title={Evaluating Lottery Tickets Under Distributional Shifts},
  author={Desai, Shrey and Zhan, Hongyuan and Aly, Ahmed},
  journal={arXiv preprint arXiv:1910.12708},
  year={2019}
}

@inproceedings{szegedy2015going,
  title={Going deeper with convolutions},
  author={Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={1--9},
  year={2015}
}

@inproceedings{van2019using,
  title={Using winning lottery tickets in transfer learning for convolutional neural networks},
  author={Van Soelen, Ryan and Sheppard, John W},
  booktitle={2019 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2019},
  organization={IEEE}
}

@article{tajbakhsh2016convolutional,
  title={Convolutional neural networks for medical image analysis: Full training or fine tuning?},
  author={Tajbakhsh, Nima and Shin, Jae Y and Gurudu, Suryakanth R and Hurst, R Todd and Kendall, Christopher B and Gotway, Michael B and Liang, Jianming},
  journal={IEEE transactions on medical imaging},
  volume={35},
  number={5},
  pages={1299--1312},
  year={2016},
  publisher={IEEE}
}

@inproceedings{he2019rethinking,
  title={Rethinking imagenet pre-training},
  author={He, Kaiming and Girshick, Ross and Doll{\'a}r, Piotr},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={4918--4927},
  year={2019}
}

@inproceedings{katharopoulos2018not,
  title={Not all samples are created equal: Deep learning with importance sampling},
  author={Katharopoulos, Angelos and Fleuret, Fran{\c{c}}ois},
  booktitle={International conference on machine learning},
  pages={2525--2534},
  year={2018},
  organization={PMLR}
}

@inproceedings{mormont2018comparison,
  title={Comparison of deep transfer learning strategies for digital pathology},
  author={Mormont, Romain and Geurts, Pierre and Mar{\'e}e, Rapha{\"e}l},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},
  pages={2262--2271},
  year={2018}
}

@article{kainz2017training,
  title={Training echo state networks for rotation-invariant bone marrow cell classification},
  author={Kainz, Philipp and Burgsteiner, Harald and Asslaber, Martin and Ahammer, Helmut},
  journal={Neural Computing and Applications},
  volume={28},
  number={6},
  pages={1277--1292},
  year={2017},
  publisher={Springer}
}

@misc{dolan2017mimo,
  title={MIMO: Musical Instrument Museums Online},
  author={Dolan, Emily I},
  year={2017},
  publisher={University of California Press}
}

@inproceedings{dong2017learning,
  title={Learning to prune deep neural networks via layer-wise optimal brain surgeon},
  author={Dong, Xin and Chen, Shangyu and Pan, Sinno},
  booktitle={Advances in Neural Information Processing Systems},
  pages={4857--4867},
  year={2017}
}

@article{paszke2017automatic,
  title={Automatic differentiation in pytorch},
  author={Paszke, Adam and Gross, Sam and Chintala, Soumith and Chanan, Gregory and Yang, Edward and DeVito, Zachary and Lin, Zeming and Desmaison, Alban and Antiga, Luca and Lerer, Adam},
  year={2017}
}

@article{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  journal={arXiv preprint arXiv:1412.6980},
  year={2014}
}

@inproceedings{abadi2016tensorflow,
  title={Tensorflow: A system for large-scale machine learning},
  author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
  booktitle={12th $\{$USENIX$\}$ symposium on operating systems design and implementation ($\{$OSDI$\}$ 16)},
  pages={265--283},
  year={2016}
}

@article{ho2021evaluation,
  title={Evaluation of transfer learning in deep convolutional neural network models for cardiac short axis slice classification},
  author={Ho, Namgyu and Kim, Yoon-Chul},
  journal={Scientific reports},
  volume={11},
  number={1},
  pages={1--11},
  year={2021},
  publisher={Nature Publishing Group}
}

@inproceedings{lin2017runtime,
  title={Runtime neural pruning},
  author={Lin, Ji and Rao, Yongming and Lu, Jiwen and Zhou, Jie},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2181--2191},
  year={2017}
}
@article{phillips2011wiki,
  title={Wiki Art Gallery, Inc.: A case for critical thinking},
  author={Phillips, Fred and Mackintosh, Brandy},
  journal={Issues in Accounting Education},
  volume={26},
  number={3},
  pages={593--608},
  year={2011},
  publisher={American Accounting Assocation}
}

@article{strezoski2018omniart,
  title={Omniart: a large-scale artistic benchmark},
  author={Strezoski, Gjorgji and Worring, Marcel},
  journal={ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)},
  volume={14},
  number={4},
  pages={1--21},
  year={2018},
  publisher={ACM New York, NY, USA}
}

@inproceedings{mensink2014rijksmuseum,
  title={The rijksmuseum challenge: Museum-centered visual recognition},
  author={Mensink, Thomas and Van Gemert, Jan},
  booktitle={Proceedings of International Conference on Multimedia Retrieval},
  pages={451--454},
  year={2014}
}


@article{strezoski2017omniart,
  title={Omniart: multi-task deep learning for artistic data analysis},
  author={Strezoski, Gjorgji and Worring, Marcel},
  journal={arXiv preprint arXiv:1708.00684},
  year={2017}
}


@article{pan2010survey,
  title={A survey on transfer learning},
  author={Pan, Sinno Jialin and Yang, Qiang},
  journal={IEEE Transactions on knowledge and data engineering},
  pages={1345--1359},
  year={2010},
  publisher={IEEE}
}

@article{mormont2020multi,
  title={Multi-task pre-training of deep neural networks for digital pathology},
  author={Mormont, Romain and Geurts, Pierre and Mar{\'e}e, Rapha{\"e}l},
  journal={IEEE journal of biomedical and health informatics},
  year={2020},
  publisher={IEEE}
}

@inproceedings{zhong2016face,
  title={Face attribute prediction using off-the-shelf CNN features},
  author={Zhong, Yang and Sullivan, Josephine and Li, Haibo},
  booktitle={2016 International Conference on Biometrics (ICB)},
  pages={1--7},
  year={2016},
  organization={IEEE}
}


@inproceedings{hernandez2018periocular,
  title={Periocular recognition using CNN features off-the-shelf},
  author={Hernandez-Diaz, Kevin and Alonso-Fernandez, Fernando and Bigun, Josef},
  booktitle={2018 International conference of the biometrics special interest group (BIOSIG)},
  pages={1--5},
  year={2018},
  organization={IEEE}
}

@inproceedings{zeiler2014visualizing,
  title={Visualizing and understanding convolutional networks},
  author={Zeiler, Matthew D and Fergus, Rob},
  booktitle={European conference on computer vision},
  pages={818--833},
  year={2014},
  organization={Springer}
}

@inproceedings{donahue2014decaf,
  title={Decaf: A deep convolutional activation feature for generic visual recognition},
  author={Donahue, Jeff and Jia, Yangqing and Vinyals, Oriol and Hoffman, Judy and Zhang, Ning and Tzeng, Eric and Darrell, Trevor},
  booktitle={International conference on machine learning},
  pages={647--655},
  year={2014},
  organization={PMLR}
}

@inproceedings{oquab2014learning,
  title={Learning and transferring mid-level image representations using convolutional neural networks},
  author={Oquab, Maxime and Bottou, Leon and Laptev, Ivan and Sivic, Josef},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={1717--1724},
  year={2014}
}

@article{zhong2020fine,
  title={Fine-art painting classification via two-channel dual path networks},
  author={Zhong, Sheng-hua and Huang, Xingsheng and Xiao, Zhijiao},
  journal={International Journal of Machine Learning and Cybernetics},
  volume={11},
  number={1},
  pages={137--152},
  year={2020},
  publisher={Springer}
}

@article{caruana1997multitask,
  title={Multitask learning},
  author={Caruana, Rich},
  journal={Machine learning},
  volume={28},
  number={1},
  pages={41--75},
  year={1997},
  publisher={Springer}
}

@inproceedings{sabatelli2018deepqv,
  title={Deep Quality-Value (DQV) Learning},
  author={Sabatelli, Matthia and Louppe, Gilles and Geurts, Pierre and Wiering, Marco},
  booktitle={Advances in Neural Information Processing Systems, Deep Reinforcement Learning Workshop},
  year={2018},
  organization={Montreal}
}

@inproceedings{sabatelli2020deep,
  title={The deep quality-value family of deep reinforcement learning algorithms},
  author={Sabatelli, Matthia and Louppe, Gilles and Geurts, Pierre and Wiering, Marco A},
  booktitle={2020 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2020},
  organization={IEEE}
}

@inproceedings{sabatelli2018deep,
  title={Deep transfer learning for art classification problems},
  author={Sabatelli, Matthia and Kestemont, Mike and Daelemans, Walter and Geurts, Pierre},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
  pages={631--646},
  year={2018}
}

@article{chollet2016xception,
  title={Xception: Deep learning with depthwise separable convolutions},
  author={Chollet, Fran{\c{c}}ois},
  journal={arXiv preprint},
  year={2016}
}

@BOOK{wollheim:1972,
  title = {{O}n Art and the Mind. {E}ssays and Lectures},
  publisher = {Allen Lane},
  year = {1972},
  author = {Wollheim, R.},
  owner = {mike},
  timestamp = {2011.12.04}
}

@article{stamatatos:2009,
author = {Stamatatos Efstathios},
title = {A survey of modern authorship attribution methods},
journal = {Journal of the American Society for Information Science and Technology},
year = {2009},
number = {3},
pages = {538-556},
doi = {10.1002/asi.21001},
}

@inproceedings{bidoiadeep,
  author    = {Francesco Bidoia and
               Matthia Sabatelli and
               Amirhossein Shantia and
               Marco A. Wiering and
               Lambert Schomaker},
  title     = {A Deep Convolutional Neural Network for Location Recognition and Geometry
               based Information},
  booktitle = {Proceedings of the 7th International Conference on Pattern Recognition
               Applications and Methods, {ICPRAM} 2018, Funchal, Madeira - Portugal,
               January 16-18, 2018.},
  pages     = {27--36},
  year      = {2018}
}


@book{goodfellow2016deep,
  title={Deep learning},
  author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
  year={2016},
  publisher={MIT press}
}

@article{rosenblatt1958perceptron,
  title={The perceptron: a probabilistic model for information storage and organization in the brain.},
  author={Rosenblatt, Frank},
  journal={Psychological review},
  volume={65},
  number={6},
  pages={386},
  year={1958},
  publisher={American Psychological Association}
}

@article{hochreiter1997long,
  title={Long short-term memory},
  author={Hochreiter, Sepp and Schmidhuber, J{\"u}rgen},
  journal={Neural computation},
  volume={9},
  number={8},
  pages={1735--1780},
  year={1997},
  publisher={MIT Press}
}

@inproceedings{maas2013rectifier,
  title={Rectifier nonlinearities improve neural network acoustic models},
  author={Maas, Andrew L and Hannun, Awni Y and Ng, Andrew Y and others},
  booktitle={Proc. icml},
  volume={30},
  number={1},
  pages={3},
  year={2013},
  organization={Citeseer}
}

@inproceedings{he2015delving,
  title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={1026--1034},
  year={2015}
}

@article{clevert2015fast,
  title={Fast and accurate deep network learning by exponential linear units (elus)},
  author={Clevert, Djork-Arn{\'e} and Unterthiner, Thomas and Hochreiter, Sepp},
  journal={arXiv preprint arXiv:1511.07289},
  year={2015}
}

@article{mcculloch1943logical,
  title={A logical calculus of the ideas immanent in nervous activity},
  author={McCulloch, Warren S and Pitts, Walter},
  journal={The bulletin of mathematical biophysics},
  volume={5},
  number={4},
  pages={115--133},
  year={1943},
  publisher={Springer}
}

@inproceedings{zhou1988computation,
  title={Computation of optical flow using a neural network.},
  author={Zhou, Yi-Tong and Chellappa, Rama},
  booktitle={ICNN},
  pages={71--78},
  year={1988}
}

@article{allen2000collaboration,
  title={Collaboration through the Colorado digitization project},
  author={Allen, Nancy},
  journal={First Monday},
  volume={5},
  number={6},
  year={2000}
}

@inproceedings{bengio2012deep,
  title={Deep learning of representations for unsupervised and transfer learning},
  author={Bengio, Yoshua},
  booktitle={Proceedings of ICML Workshop on Unsupervised and Transfer Learning},
  pages={17--36},
  year={2012}
}

@misc{raghakotkerasvis,
  title={keras-vis},
  author={Kotikalapudi, Raghavendra and contributors},
  year={2017},
  publisher={GitHub},
  howpublished={\url{https://github.com/raghakot/keras-vis}},
}

@article{masters2018revisiting,
  title={Revisiting Small Batch Training for Deep Neural Networks},
  author={Masters, Dominic and Luschi, Carlo},
  journal={arXiv preprint arXiv:1804.07612},
  year={2018}
}

@inproceedings{szegedy2016rethinking,
  title={Rethinking the inception architecture for computer vision},
  author={Szegedy, Christian and Vanhoucke, Vincent and Ioffe, Sergey and Shlens, Jon and Wojna, Zbigniew},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={2818--2826},
  year={2016}
}

@article{simonyan2014very,
  title={Very deep convolutional networks for large-scale image recognition},
  author={Simonyan, Karen and Zisserman, Andrew},
  journal={arXiv preprint arXiv:1409.1556},
  year={2014}
}

@article{geurts2006extremely,
  title={Extremely randomized trees},
  author={Geurts, Pierre and Ernst, Damien and Wehenkel, Louis},
  journal={Machine learning},
  volume={63},
  number={1},
  pages={3--42},
  year={2006},
  publisher={Springer}
}

@misc{chollet2015keras,
  title={Keras},
  author={Chollet, Fran{\c{c}}ois and others},
  year={2015}
}

@article{pedregosa2011scikit,
  title={Scikit-learn: Machine learning in Python},
  author={Pedregosa, Fabian and Varoquaux, Ga{\"e}l and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and others},
  journal={Journal of machine learning research},
  volume={12},
  number={Oct},
  pages={2825--2830},
  year={2011}
}

@article{lecun2015deep,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={nature},
  volume={521},
  number={7553},
  pages={436},
  year={2015},
  publisher={Nature Publishing Group}
}

@techreport{weibel1998dublin,
  title={Dublin core metadata for resource discovery},
  author={Weibel, Stuart and Kunze, John and Lagoze, Carl and Wolf, Misha},
  year={1998}
}

@inproceedings{krizhevsky2012imagenet,
  title={Imagenet classification with deep convolutional neural networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  booktitle={Advances in neural information processing systems},
  pages={1097--1105},
  year={2012}
}

@inproceedings{huang2017densely,
  title={Densely connected convolutional networks},
  author={Huang, Gao and Liu, Zhuang and Weinberger, Kilian Q and van der Maaten, Laurens},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  volume={1},
  number={2},
  year={2017}
}

@article{parry2005digital,
  title={Digital heritage and the rise of theory in museum computing},
  author={Parry, Ross},
  journal={Museum management and Curatorship},
  pages={333--348},
  year={2005},
  publisher={Elsevier}
}

@inproceedings{szegedy2017inception,
  title={Inception-v4, inception-resnet and the impact of residual connections on learning},
  author={Szegedy, Christian and Ioffe, Sergey and Vanhoucke, Vincent and Alemi, Alexander A},
  booktitle={Thirty-first AAAI conference on artificial intelligence},
  year={2017}
}

@inproceedings{tan2019efficientnet,
  title={Efficientnet: Rethinking model scaling for convolutional neural networks},
  author={Tan, Mingxing and Le, Quoc},
  booktitle={International Conference on Machine Learning},
  pages={6105--6114},
  year={2019},
  organization={PMLR}
}

@article{bryson1975applied,
  title={Applied optimal control: Optimization},
  author={Bryson, Arthur E},
  journal={Estimization and Control},
  volume={2},
  year={1975},
  publisher={Hemisphere}
}

@article{mitchell1997machine,
  title={Machine learning},
  author={Mitchell, Tom M and others},
  year={1997},
  publisher={McGraw-hill New York}
}

@article{patel2019improved,
  title={Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game},
  author={Patel, Devdhar and Hazan, Hananel and Saunders, Daniel J and Siegelmann, Hava T and Kozma, Robert},
  journal={Neural Networks},
  volume={120},
  pages={108--115},
  year={2019},
  publisher={Elsevier}
}

@inproceedings{sandler2018mobilenetv2,
  title={Mobilenetv2: Inverted residuals and linear bottlenecks},
  author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={4510--4520},
  year={2018}
}

@book{aggarwal2018neural,
  title={Neural networks and deep learning},
  author={Aggarwal, Charu C and others},
  year={2018},
  publisher={Springer}
}

@inproceedings{howard2019searching,
  title={Searching for mobilenetv3},
  author={Howard, Andrew and Sandler, Mark and Chu, Grace and Chen, Liang-Chieh and Chen, Bo and Tan, Mingxing and Wang, Weijun and Zhu, Yukun and Pang, Ruoming and Vasudevan, Vijay and others},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={1314--1324},
  year={2019}
}

@inproceedings{graves2006connectionist,
  title={Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks},
  author={Graves, Alex and Fern{\'a}ndez, Santiago and Gomez, Faustino and Schmidhuber, J{\"u}rgen},
  booktitle={Proceedings of the 23rd international conference on Machine learning},
  pages={369--376},
  year={2006}
}

@incollection{vapnik2015uniform,
  title={On the uniform convergence of relative frequencies of events to their probabilities},
  author={Vapnik, Vladimir N and Chervonenkis, A Ya},
  booktitle={Measures of complexity},
  pages={11--30},
  year={2015},
  publisher={Springer}
}

@phdthesis{vanjos2017deep,
  title={Deep Reinforcement Learnig of Video Games},
  author={van de Wolfshaar, Jos},
  year={2017},
  school={Faculty of Science and Engineering}
}

@inproceedings{vanjos2018deep,
  title={Deep Learning Policy Quantization.},
  author={van de Wolfshaar, Jos and Wiering, Marco A and Schomaker, Lambert},
  year={2018}
}

@article{aittahar2020empirical,
  title={Empirical Analysis of Policy Gradient Algorithms where Starting States are Sampled accordingly to Most Frequently Visited States},
  author={Aittahar, Samy and Fonteneau, Rapha{\"e}l and Ernst, Damien},
  journal={IFAC-PapersOnLine},
  volume={53},
  number={2},
  pages={8097--8104},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{mnih2014recurrent,
  title={Recurrent models of visual attention},
  author={Mnih, Volodymyr and Heess, Nicolas and Graves, Alex and others},
  booktitle={Advances in neural information processing systems},
  pages={2204--2212},
  year={2014}
}

@inproceedings{goodfellow2013maxout,
  title={Maxout networks},
  author={Goodfellow, Ian and Warde-Farley, David and Mirza, Mehdi and Courville, Aaron and Bengio, Yoshua},
  booktitle={International conference on machine learning},
  pages={1319--1327},
  year={2013},
  organization={PMLR}
}

@inproceedings{razavian2014cnn,
  title={CNN features off-the-shelf: an astounding baseline for recognition},
  author={Razavian, Ali Sharif and Azizpour, Hossein and Sullivan, Josephine and Carlsson, Stefan},
  booktitle={Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on},
  pages={512--519},
  year={2014},
  organization={IEEE}
}

@inproceedings{reyes2015fine,
  title={Fine-tuning Deep Convolutional Networks for Plant Recognition.},
  author={Reyes, Angie K and Caicedo, Juan C and Camargo, Jorge E},
  booktitle={CLEF (Working Notes)},
  year={2015}
}

@inproceedings{van2015deep,
  title={Deep convolutional neural networks and support vector machines for gender recognition},
  author={van de Wolfshaar, Jos and Karaaba, Mahir F and Wiering, Marco A},
  booktitle={Computational Intelligence, 2015 IEEE Symposium Series on},
  pages={188--195},
  year={2015},
  organization={IEEE}
}

@article{sermanet2013overfeat,
  title={Overfeat: Integrated recognition, localization and detection using convolutional networks},
  author={Sermanet, Pierre and Eigen, David and Zhang, Xiang and Mathieu, Micha{\"e}l and Fergus, Rob and LeCun, Yann},
  journal={arXiv preprint arXiv:1312.6229},
  year={2013}
}

@article{tome2016deep,
  title={Deep convolutional neural networks for pedestrian detection},
  author={Tom{\`e}, Denis and Monti, Federico and Baroffio, Luca and Bondi, Luca and Tagliasacchi, Marco and Tubaro, Stefano},
  journal={Signal Processing: Image Communication},
  pages={482--489},
  year={2016},
  publisher={Elsevier}
}

@inproceedings{ma2015multimodal,
  title={Multimodal convolutional neural networks for matching image and sentence},
  author={Ma, Lin and Lu, Zhengdong and Shang, Lifeng and Li, Hang},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={2623--2631},
  year={2015}
}

@inproceedings{xie2017aggregated,
  title={Aggregated residual transformations for deep neural networks},
  author={Xie, Saining and Girshick, Ross and Doll{\'a}r, Piotr and Tu, Zhuowen and He, Kaiming},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on},
  pages={5987--5995},
  year={2017},
  organization={IEEE}
}

@article{duchi2011adaptive,
  title={Adaptive subgradient methods for online learning and stochastic optimization.},
  author={Duchi, John and Hazan, Elad and Singer, Yoram},
  journal={Journal of machine learning research},
  volume={12},
  number={7},
  year={2011}
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle={Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on},
  pages={248--255},
  year={2009},
  organization={IEEE}
} 

@techreport{huang2007labeled,
  title={Labeled faces in the wild: A database for studying face recognition in unconstrained environments},
  author={Huang, Gary B and Ramesh, Manu and Berg, Tamara and Learned-Miller, Erik},
  year={2007},
  institution={Technical Report 07-49, University of Massachusetts, Amherst}
}

@inproceedings{stallkamp2011german,
  title={The German traffic sign recognition benchmark: a multi-class classification competition},
  author={Stallkamp, Johannes and Schlipsing, Marc and Salmen, Jan and Igel, Christian},
  booktitle={Neural Networks (IJCNN), The 2011 International Joint Conference on},
  pages={1453--1460},
  year={2011},
  organization={IEEE}
}

@article{bojarski2016visualbackprop,
  title={VisualBackProp: efficient visualization of CNNs},
  author={Bojarski, Mariusz and Choromanska, Anna and Choromanski, Krzysztof and Firner, Bernhard and Jackel, Larry and Muller, Urs and Zieba, Karol},
  journal={arXiv preprint arXiv:1611.05418},
  year={2016}
}

@inproceedings{caruana2001overfitting,
  title={Overfitting in neural nets: Backpropagation, conjugate gradient, and early stopping},
  author={Caruana, Rich and Lawrence, Steve and Giles, C Lee},
  booktitle={Advances in neural information processing systems},
  pages={402--408},
  year={2001}
}

@article{peters2019tune,
  title={To tune or not to tune? adapting pretrained representations to diverse tasks},
  author={Peters, Matthew E and Ruder, Sebastian and Smith, Noah A},
  journal={arXiv preprint arXiv:1903.05987},
  year={2019}
}

@article{peters2018deep,
  title={Deep contextualized word representations},
  author={Peters, Matthew E and Neumann, Mark and Iyyer, Mohit and Gardner, Matt and Clark, Christopher and Lee, Kenton and Zettlemoyer, Luke},
  journal={arXiv preprint arXiv:1802.05365},
  year={2018}
}

@inproceedings{deng2013new,
  title={New types of deep neural network learning for speech recognition and related applications: An overview},
  author={Deng, Li and Hinton, Geoffrey and Kingsbury, Brian},
  booktitle={2013 IEEE international conference on acoustics, speech and signal processing},
  pages={8599--8603},
  year={2013},
  organization={IEEE}
}

@article{george2017deep,
  title={Deep Transfer Learning: A new deep learning glitch classification method for advanced LIGO},
  author={George, Daniel and Shen, Hongyu and Huerta, EA},
  journal={arXiv preprint arXiv:1706.07446},
  year={2017}
}

@article{kong2020panns,
  title={Panns: Large-scale pretrained audio neural networks for audio pattern recognition},
  author={Kong, Qiuqiang and Cao, Yin and Iqbal, Turab and Wang, Yuxuan and Wang, Wenwu and Plumbley, Mark D},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  volume={28},
  pages={2880--2894},
  year={2020},
  publisher={IEEE}
}

@inproceedings{boulanger2013audio,
  title={Audio Chord Recognition with Recurrent Neural Networks.},
  author={Boulanger-Lewandowski, Nicolas and Bengio, Yoshua and Vincent, Pascal},
  booktitle={ISMIR},
  pages={335--340},
  year={2013},
  organization={Citeseer}
}

@inproceedings{houlsby2019parameter,
  title={Parameter-efficient transfer learning for NLP},
  author={Houlsby, Neil and Giurgiu, Andrei and Jastrzebski, Stanislaw and Morrone, Bruna and De Laroussilhe, Quentin and Gesmundo, Andrea and Attariyan, Mona and Gelly, Sylvain},
  booktitle={International Conference on Machine Learning},
  pages={2790--2799},
  year={2019},
  organization={PMLR}
}

@article{howard2018universal,
  title={Universal language model fine-tuning for text classification},
  author={Howard, Jeremy and Ruder, Sebastian},
  journal={arXiv preprint arXiv:1801.06146},
  year={2018}
}

@article{zarrella2016mitre,
  title={Mitre at semeval-2016 task 6: Transfer learning for stance detection},
  author={Zarrella, Guido and Marsh, Amy},
  journal={arXiv preprint arXiv:1606.03784},
  year={2016}
}

@article{ackermann2018using,
  title={Using transfer learning to detect galaxy mergers},
  author={Ackermann, Sandro and Schawinksi, Kevin and Zhang, Ce and Weigel, Anna K and Turp, M Dennis},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2018}
}

@article{dominguez2019transfer,
  title={Transfer learning for galaxy morphology from one survey to another},
  author={Dom{\'\i}nguez S{\'a}nchez, H and Huertas-Company, M and Bernardi, M and Kaviraj, S and Fischer, JL and Abbott, TMC and Abdalla, FB and Annis, J and Avila, S and Brooks, D and others},
  journal={Monthly Notices of the Royal Astronomical Society},
  volume={484},
  number={1},
  pages={93--100},
  year={2019},
  publisher={Oxford University Press}
}

@article{kornblith2018better,
  title={Do Better ImageNet Models Transfer Better?},
  author={Kornblith, Simon and Shlens, Jonathon and Le, Quoc V},
  journal={arXiv preprint arXiv:1805.08974},
  year={2018}
}

@inproceedings{hasselt2010double,
  title={Double {Q}-learning},
  author={Van Hasselt, Hado},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2613--2621},
  year={2010}
}

@article{van2004rational,
  title={Rational overoptimism (and other biases)},
  author={Van den Steen, Eric},
  journal={American Economic Review},
  volume={94},
  number={4},
  pages={1141--1151},
  year={2004}
}

@article{smith2006optimizer,
  title={The optimizer’s curse: Skepticism and postdecision surprise in decision analysis},
  author={Smith, James E and Winkler, Robert L},
  journal={Management Science},
  volume={52},
  number={3},
  pages={311--322},
  year={2006},
  publisher={INFORMS}
}

@article{mnih2015human,
  title={Human-level control through deep reinforcement learning},
  author={Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg and others},
  journal={Nature},
  volume={518},
  number={7540},
  pages={529},
  year={2015},
  publisher={Nature Publishing Group}
}

@article{srivastava2014dropout,
  title={Dropout: a simple way to prevent neural networks from overfitting},
  author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
  journal={The journal of machine learning research},
  volume={15},
  number={1},
  pages={1929--1958},
  year={2014},
  publisher={JMLR. org}
}

@article{sutton1984temporal,
  title={Temporal credit assignment in reinforcement learning},
  author={Sutton, Richard Stuart},
  year={1984}
}

@article{fortunato2017noisy,
  title={Noisy networks for exploration},
  author={Fortunato, Meire and Azar, Mohammad Gheshlaghi and Piot, Bilal and Menick, Jacob and Osband, Ian and Graves, Alex and Mnih, Vlad and Munos, Remi and Hassabis, Demis and Pietquin, Olivier and others},
  journal={arXiv preprint arXiv:1706.10295},
  year={2017}
}

@article{schaul2015prioritized,
  title={Prioritized experience replay},
  author={Schaul, Tom and Quan, John and Antonoglou, Ioannis and Silver, David},
  journal={arXiv preprint arXiv:1511.05952},
  year={2015}
}

@article{schmidhuber2015deep,
  title={Deep learning in neural networks: An overview},
  author={Schmidhuber, J{\"u}rgen},
  journal={Neural networks},
  volume={61},
  pages={85--117},
  year={2015},
  publisher={Elsevier}
}

@article{mnih2013playing,
  title={Playing atari with deep reinforcement learning},
  author={Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Graves, Alex and Antonoglou, Ioannis and Wierstra, Daan and Riedmiller, Martin},
  journal={arXiv preprint arXiv:1312.5602},
  year={2013}
}

@inproceedings{boyan1995generalization,
  title={Generalization in reinforcement learning: Safely approximating the value function},
  author={Boyan, Justin A and Moore, Andrew W},
  booktitle={Advances in neural information processing systems},
  pages={369--376},
  year={1995}
}

@phdthesis{wiering1999explorations,
  title={Explorations in efficient reinforcement learning},
  author={Wiering, Marco A},
  year={1999},
  school={University of Amsterdam}
}

@inproceedings{henderson2018deep,
  title={Deep reinforcement learning that matters},
  author={Henderson, Peter and Islam, Riashat and Bachman, Philip and Pineau, Joelle and Precup, Doina and Meger, David},
  booktitle={Thirty-Second AAAI Conference on Artificial Intelligence},
  year={2018}
}

@article{castro2018dopamine,
  title={Dopamine: A research framework for deep reinforcement learning},
  author={Castro, Pablo Samuel and Moitra, Subhodeep and Gelada, Carles and Kumar, Saurabh and Bellemare, Marc G},
  journal={arXiv preprint arXiv:1812.06110},
  year={2018}
}

@article{thrun1992efficient,
  title={Efficient exploration in reinforcement learning},
  author={Thrun, Sebastian B},
  year={1992},
  publisher={Citeseer}
}

@inproceedings{kendall2018multi,
  title={Multi-task learning using uncertainty to weigh losses for scene geometry and semantics},
  author={Kendall, Alex and Gal, Yarin and Cipolla, Roberto},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={7482--7491},
  year={2018}
}

@inproceedings{he2017mask,
  title={Mask r-cnn},
  author={He, Kaiming and Gkioxari, Georgia and Doll{\'a}r, Piotr and Girshick, Ross},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={2961--2969},
  year={2017}
}

@inproceedings{huang2018yolo,
  title={YOLO-LITE: a real-time object detection algorithm optimized for non-GPU computers},
  author={Huang, Rachel and Pedoeem, Jonathan and Chen, Cuixian},
  booktitle={2018 IEEE International Conference on Big Data (Big Data)},
  pages={2503--2510},
  year={2018},
  organization={IEEE}
}

@inproceedings{redmon2016you,
  title={You only look once: Unified, real-time object detection},
  author={Redmon, Joseph and Divvala, Santosh and Girshick, Ross and Farhadi, Ali},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={779--788},
  year={2016}
}

@article{minaee2021image,
  title={Image segmentation using deep learning: A survey},
  author={Minaee, Shervin and Boykov, Yuri Y and Porikli, Fatih and Plaza, Antonio J and Kehtarnavaz, Nasser and Terzopoulos, Demetri},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2021},
  publisher={IEEE}
}

@inproceedings{girshick2014rich,
  title={Rich feature hierarchies for accurate object detection and semantic segmentation},
  author={Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={580--587},
  year={2014}
}

@article{ren2015faster,
  title={Faster r-cnn: Towards real-time object detection with region proposal networks},
  author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
  journal={Advances in neural information processing systems},
  volume={28},
  pages={91--99},
  year={2015}
}

@article{jiao2019survey,
  title={A survey of deep learning-based object detection},
  author={Jiao, Licheng and Zhang, Fan and Liu, Fang and Yang, Shuyuan and Li, Lingling and Feng, Zhixi and Qu, Rong},
  journal={IEEE access},
  volume={7},
  pages={128837--128868},
  year={2019},
  publisher={IEEE}
}

@book{busoniu2010reinforcement,
  title={Reinforcement learning and dynamic programming using function approximators},
  author={Busoniu, Lucian and Babuska, Robert and De Schutter, Bart and Ernst, Damien},
  volume={39},
  year={2010},
  publisher={CRC press}
}

@article{vanseijen2019using,
  title={Using a logarithmic mapping to enable lower discount factors in reinforcement learning},
  author={Van Seijen, Harm and Fatemi, Mehdi and Tavakoli, Arash},
  journal={arXiv preprint arXiv:1906.00572},
  year={2019}
}

@inproceedings{franccois2015discount,
  title={How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies},
  author={Fran{\c{c}}ois-Lavet, Vincent and Fonteneau, Rapha{\"e}l and Ernst, Damien},
  booktitle={NIPS 2015 Workshop on Deep Reinforcement Learning},
  year={2015}
}

@book{sutton2018reinforcement,
  title={Reinforcement learning: An introduction},
  author={Sutton, Richard S and Barto, Andrew G},
  year={2018},
  publisher={MIT press}
}

@inproceedings{van2016deep,
  title={Deep reinforcement learning with double {Q}-learning},
  author={Van Hasselt, Hado and Guez, Arthur and Silver, David},
  booktitle={Thirtieth AAAI Conference on Artificial Intelligence},
  year={2016}
}

@article{bellman1966dynamic,
  title={Dynamic programming},
  author={Bellman, Richard},
  journal={Science},
  volume={153},
  number={3731},
  pages={34--37},
  year={1966},
  publisher={American Association for the Advancement of Science}
}

@article{marklundexact,
  title={Exact (Then Approximate) Dynamic Programming for Deep Reinforcement Learning},
  author={Marklund, Henrik and Nair, Suraj and Finn, Chelsea}
}

@article{kumar2019stabilizing,
  title={Stabilizing off-policy q-learning via bootstrapping error reduction},
  author={Kumar, Aviral and Fu, Justin and Tucker, George and Levine, Sergey},
  journal={arXiv preprint arXiv:1906.00949},
  year={2019}
}

@article{kipf2016semi,
  title={Semi-supervised classification with graph convolutional networks},
  author={Kipf, Thomas N and Welling, Max},
  journal={arXiv preprint arXiv:1609.02907},
  year={2016}
}

@article{adadi2021survey,
  title={A survey on data-efficient algorithms in big data era},
  author={Adadi, Amina},
  journal={Journal of Big Data},
  volume={8},
  number={1},
  pages={1--54},
  year={2021},
  publisher={Springer}
}

@article{marcus2018deep,
  title={Deep learning: A critical appraisal},
  author={Marcus, Gary},
  journal={arXiv preprint arXiv:1801.00631},
  year={2018}
}

@inproceedings{scarselli2005graph,
  title={Graph neural networks for ranking web pages},
  author={Scarselli, Franco and Yong, Sweah Liang and Gori, Marco and Hagenbuchner, Markus and Tsoi, Ah Chung and Maggini, Marco},
  booktitle={The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)},
  pages={666--672},
  year={2005},
  organization={IEEE}
}

@article{garcia2017few,
  title={Few-shot learning with graph neural networks},
  author={Garcia, Victor and Bruna, Joan},
  journal={arXiv preprint arXiv:1711.04043},
  year={2017}
}

@article{scarselli2008graph,
  title={The graph neural network model},
  author={Scarselli, Franco and Gori, Marco and Tsoi, Ah Chung and Hagenbuchner, Markus and Monfardini, Gabriele},
  journal={IEEE transactions on neural networks},
  volume={20},
  number={1},
  pages={61--80},
  year={2008},
  publisher={IEEE}
}

@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}

@inproceedings{anschel2017averaged,
  title={Averaged-dqn: Variance reduction and stabilization for deep reinforcement learning},
  author={Anschel, Oron and Baram, Nir and Shimkin, Nahum},
  booktitle={International conference on machine learning},
  pages={176--185},
  year={2017},
  organization={PMLR}
}

@book{van2011insights,
  title={Insights in reinforcement rearning: formal analysis and empirical evaluation of temporal-difference learning algorithms},
  author={van Hasselt, Hado Philip},
  year={2011},
  publisher={Utrecht University}
}

@article{schmidhuber2019reinforcement,
  title={Reinforcement Learning Upside Down: Don't Predict Rewards--Just Map Them to Actions},
  author={Schmidhuber, Juergen},
  journal={arXiv preprint arXiv:1912.02875},
  year={2019}
}


@article{li2017deep,
  title={Deep reinforcement learning: An overview},
  author={Li, Yuxi},
  journal={arXiv preprint arXiv:1701.07274},
  year={2017}
}

@inproceedings{wiering2005qv,
  title={{QV} (lambda)-learning: A new on-policy reinforcement learning algorithm},
  author={Wiering, Marco A},
  booktitle={Proceedings of the 7th European Workshop on Reinforcement Learning},
  pages={17--18},
  year={2005}
}

@article{mott2019towards,
  title={Towards interpretable reinforcement learning using attention augmented agents},
  author={Mott, Alex and Zoran, Daniel and Chrzanowski, Mike and Wierstra, Daan and Rezende, Danilo J},
  journal={arXiv preprint arXiv:1906.02500},
  year={2019}
}

@article{fujimoto2019benchmarking,
  title={Benchmarking Batch Deep Reinforcement Learning Algorithms},
  author={Fujimoto, Scott and Conti, Edoardo and Ghavamzadeh, Mohammad and Pineau, Joelle},
  journal={arXiv preprint arXiv:1910.01708},
  year={2019}
}

@article{srivastava2019training,
  title={Training agents using upside-down reinforcement learning},
  author={Srivastava, Rupesh Kumar and Shyam, Pranav and Mutz, Filipe and Ja{\'s}kowski, Wojciech and Schmidhuber, J{\"u}rgen},
  journal={arXiv preprint arXiv:1912.02877},
  year={2019}
}

@article{sabatelli2019approximating,
  title={Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms},
  author={Sabatelli, Matthia and Louppe, Gilles and Geurts, Pierre and Wiering, Marco A},
  journal={arXiv preprint arXiv:1909.01779},
  year={2019}
}

@article{sabatelli2019improving,
  title={Improving the Training of Deep Convolutional Neural Networks for Art Classification: from Transfer Learning to Multi-Task Learning},
  author={Sabatelli, Matthia and Kestemont, Mike and Geurts, Pierre},
  year={2019}
}

@inproceedings{hammond2020forest,
  title={Forest Fire Control with Learning from Demonstration and Reinforcement Learning},
  author={Hammond, Travis and Schaap, Dirk Jelle and Sabatelli, Matthia and Wiering, Marco A},
  booktitle={2020 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2020},
  organization={IEEE}
}

@article{keskar2016large,
  title={On large-batch training for deep learning: Generalization gap and sharp minima},
  author={Keskar, Nitish Shirish and Mudigere, Dheevatsa and Nocedal, Jorge and Smelyanskiy, Mikhail and Tang, Ping Tak Peter},
  journal={arXiv preprint arXiv:1609.04836},
  year={2016}
}

@article{radiuk2017impact,
  title={Impact of training set batch size on the performance of convolutional neural networks for diverse datasets},
  author={Radiuk, Pavlo M and others},
  journal={Information Technology and Management Science},
  volume={20},
  number={1},
  pages={20--24},
  year={2017},
  publisher={Sciendo}
}

@article{kandel2020effect,
  title={The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset},
  author={Kandel, Ibrahem and Castelli, Mauro},
  journal={ICT express},
  volume={6},
  number={4},
  pages={312--315},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{sabatelli2018learning,
  title={Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead},
  author={Sabatelli, Matthia and Bidoia, Francesco and Codreanu, Valeriu and Wiering, Marco},
  booktitle={7th International Conference on Pattern Recognition Applications and Methods},
  year={2018}
}

@article{banartransfer,
  title={Transfer Learning with Style Transfer between the Photorealis-tic and Artistic Domain},
  author={Banar, Nikolay and Sabatelli, Matthia and Geurts, Pierre and Daelemans, Walter and Kestemont, Mike},
  year={2021}
}

@article{green2013ridim,
  title={RIdIM: cataloguing music iconography since 1971},
  author={Green, Alan and Ferguson, Sean},
  journal={Fontes artis musicae},
  pages={1--8},
  year={2013},
  publisher={JSTOR}
}

@inproceedings{leroy21qvmix,
  title={QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning},
  author={Leroy, Pascal and Ernst, Damien and Geurts, Pierre and Louppe, Gilles and Pisane, Jonathan and Sabatelli, Matthia},
  booktitle={Proceedings of the AAAI-21 Workshop on Reinforcement Learning in Games},
  pages={8}
}

@article{moore1990efficient,
  title={Efficient memory-based learning for robot control},
  author={Moore, Andrew William},
  year={1990},
  publisher={Citeseer}
}

@inproceedings{bucsoniu2011approximate,
  title={Approximate reinforcement learning: An overview},
  author={Bu{\c{s}}oniu, Lucian and Ernst, Damien and De Schutter, Bart and Babu{\v{s}}ka, Robert},
  booktitle={2011 IEEE symposium on adaptive dynamic programming and reinforcement learning (ADPRL)},
  pages={1--8},
  year={2011},
  organization={IEEE}
}

@inproceedings{wiering2009qv,
  title={The {QV} family compared to other reinforcement learning algorithms},
  author={Wiering, Marco A and Van Hasselt, Hado},
  booktitle={Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL'09. IEEE Symposium on},
  pages={101--108},
  year={2009},
  organization={IEEE}
}

@article{sutton1988learning,
  title={Learning to predict by the methods of temporal differences},
  author={Sutton, Richard S},
  journal={Machine learning},
  volume={3},
  number={1},
  pages={9--44},
  year={1988},
  publisher={Springer}
}

@inproceedings{wang2016dueling,
  title={Dueling Network Architectures for Deep Reinforcement Learning},
  author={Wang, Ziyu and Schaul, Tom and Hessel, Matteo and Van Hasselt, Hado and Lanctot, Marc and Freitas, Nando},
  booktitle={International Conference on Machine Learning},
  pages={1995--2003},
  year={2016}
}

@article{kirkpatrick2017overcoming,
  title={Overcoming catastrophic forgetting in neural networks},
  author={Kirkpatrick, James and Pascanu, Razvan and Rabinowitz, Neil and Veness, Joel and Desjardins, Guillaume and Rusu, Andrei A and Milan, Kieran and Quan, John and Ramalho, Tiago and Grabska-Barwinska, Agnieszka and others},
  journal={Proceedings of the national academy of sciences},
  volume={114},
  number={13},
  pages={3521--3526},
  year={2017},
  publisher={National Acad Sciences}
}


@article{schaal2004estimating,
  title={Estimating future reward in reinforcement learning animats using associative learning},
  author={Schaal, Stefan and Ijspeert, Auke Jan and Billard, Aude and Vijayakumar, Sethu and Meyer, Jean-Arcady},
  year={2004},
  publisher={MIT Press}
}

@inproceedings{konidaris2006autonomous,
  title={Autonomous shaping: Knowledge transfer in reinforcement learning},
  author={Konidaris, George and Barto, Andrew},
  booktitle={Proceedings of the 23rd international conference on Machine learning},
  pages={489--496},
  year={2006}
}

@article{sabatelli2021advances,
  title={Advances in Digital Music Iconography: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain.},
  author={Sabatelli, Matthia and Banar, Nikolay and Cocriamont, Marie and Coudyzer, Eva and Lasaracina, Karine and Daelemans, Walter and Geurts, Pierre and Kestemont, Mike},
  journal={DHQ: Digital Humanities Quarterly},
  volume={15},
  number={1},
  year={2021}
}

@techreport{singh2005intrinsically,
  title={Intrinsically motivated reinforcement learning},
  author={Singh, Satinder and Barto, Andrew G and Chentanez, Nuttapong},
  year={2005},
  institution={MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE}
}

@inproceedings{hessel2018rainbow,
  title={Rainbow: Combining improvements in deep reinforcement learning},
  author={Hessel, Matteo and Modayil, Joseph and Van Hasselt, Hado and Schaul, Tom and Ostrovski, Georg and Dabney, Will and Horgan, Dan and Piot, Bilal and Azar, Mohammad and Silver, David},
  booktitle={Thirty-Second AAAI Conference on Artificial Intelligence},
  year={2018}
}

@inproceedings{sutton1996generalization,
  title={Generalization in reinforcement learning: Successful examples using sparse coarse coding},
  author={Sutton, Richard S},
  booktitle={Advances in neural information processing systems},
  pages={1038--1044},
  year={1996}
}

@inproceedings{silver2001selective,
  title={Selective functional transfer: Inductive bias from related tasks},
  author={Silver, Daniel and Mercer, Robert},
  booktitle={IASTED International Conference on Artificial Intelligence and Soft Computing (ASC2001)},
  pages={182--189},
  year={2001}
}

@article{pong2018temporal,
  title={Temporal difference models: Model-free deep {RL} for model-based control},
  author={Pong, Vitchyr and Gu, Shixiang and Dalal, Murtaza and Levine, Sergey},
  journal={arXiv preprint arXiv:1802.09081},
  year={2018}
}


@article{baxter2000model,
  title={A model of inductive bias learning},
  author={Baxter, Jonathan},
  journal={Journal of artificial intelligence research},
  volume={12},
  pages={149--198},
  year={2000}
}


@phdthesis{baird1993advantage,
  title={Advantage updating},
  author={Baird III, Leemon C},
  year={1993},
  institution={Wright Lab Wright-Patterson AFB OH}
}

@article{bellemare2013arcade,
  title={The arcade learning environment: An evaluation platform for general agents},
  author={Bellemare, Marc G and Naddaf, Yavar and Veness, Joel and Bowling, Michael},
  journal={Journal of Artificial Intelligence Research},
  volume={47},
  pages={253--279},
  year={2013}
}

@article{puterman1990markov,
  title={Markov decision processes},
  author={Puterman, Martin L},
  journal={Handbooks in operations research and management science},
  volume={2},
  pages={331--434},
  year={1990},
  publisher={Elsevier}
}

@book{puterman2014markov,
  title={Markov decision processes: discrete stochastic dynamic programming},
  author={Puterman, Martin L},
  year={2014},
  publisher={John Wiley \& Sons}
}

@book{bertsekas2000dynamic,
  title={Dynamic programming and optimal control: Vol. 1},
  author={Bertsekas, Dimitri P and others},
  year={2000},
  publisher={Athena scientific Belmont}
}

@inproceedings{bertsekas1995neuro,
  title={Neuro-dynamic programming: an overview},
  author={Bertsekas, Dimitri P and Tsitsiklis, John N},
  booktitle={Proceedings of 1995 34th IEEE conference on decision and control},
  volume={1},
  pages={560--564},
  year={1995},
  organization={IEEE}
}

@article{bertsekas2015value,
  title={Value and policy iterations in optimal control and adaptive dynamic programming},
  author={Bertsekas, Dimitri P},
  journal={IEEE transactions on neural networks and learning systems},
  volume={28},
  number={3},
  pages={500--509},
  year={2015},
  publisher={IEEE}
}

@article{wei2015value,
  title={Value iteration adaptive dynamic programming for optimal control of discrete-time nonlinear systems},
  author={Wei, Qinglai and Liu, Derong and Lin, Hanquan},
  journal={IEEE Transactions on cybernetics},
  volume={46},
  number={3},
  pages={840--853},
  year={2015},
  publisher={IEEE}
}

@book{bertsekas2019reinforcement,
  title={Reinforcement learning and optimal control},
  author={Bertsekas, Dimitri P},
  year={2019},
  publisher={Athena Scientific Belmont, MA}
}


@inproceedings{zhao2016deep,
  title={Deep reinforcement learning with experience replay based on {SARSA}},
  author={Zhao, Dongbin and Wang, Haitao and Shao, Kun and Zhu, Yuanheng},
  booktitle={2016 IEEE Symposium Series on Computational Intelligence (SSCI)},
  pages={1--6},
  year={2016},
  organization={IEEE}
}

@inproceedings{lu2018non,
  title={Non-delusional {Q}-learning and value-iteration},
  author={Lu, Tyler and Schuurmans, Dale and Boutilier, Craig},
  booktitle={Advances in Neural Information Processing Systems},
  pages={9971--9981},
  year={2018}
}

@article{van2018deep_triad,
  title={Deep Reinforcement Learning and the Deadly Triad},
  author={Van Hasselt, Hado and Doron, Yotam and Strub, Florian and Hessel, Matteo and Sonnerat, Nicolas and Modayil, Joseph},
  journal={arXiv preprint arXiv:1812.02648},
  year={2018}
}

@article{claes2021deep,
  title={Deep Learning for the Classification and Detection of Animals in Artworks},
  author={Claes, Yann and others},
  year={2021},
  publisher={Universit{\'e} de Li{\`e}ge, Li{\`e}ge, Belgique}
}

@inproceedings{girshick2015fast,
  title={Fast r-cnn},
  author={Girshick, Ross},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={1440--1448},
  year={2015}
}

@inproceedings{fedus2020revisiting,
  title={Revisiting fundamentals of experience replay},
  author={Fedus, William and Ramachandran, Prajit and Agarwal, Rishabh and Bengio, Yoshua and Larochelle, Hugo and Rowland, Mark and Dabney, Will},
  booktitle={International Conference on Machine Learning},
  pages={3061--3071},
  year={2020},
  organization={PMLR}
}

@article{watkins1992q,
  title={Q-learning},
  author={Watkins, Christopher JCH and Dayan, Peter},
  journal={Machine learning},
  volume={8},
  number={3-4},
  pages={279--292},
  year={1992},
  publisher={Springer}
}

@article{barto1983neuronlike,
  title={Neuronlike adaptive elements that can solve difficult learning control problems},
  author={Barto, Andrew G and Sutton, Richard S and Anderson, Charles W},
  journal={IEEE transactions on systems, man, and cybernetics},
  number={5},
  pages={834--846},
  year={1983},
  publisher={IEEE}
}


@book{rummery1994line,
  title={On-line Q-learning using connectionist systems},
  author={Rummery, Gavin A and Niranjan, Mahesan},
  volume={37},
  year={1994},
  publisher={University of Cambridge, Department of Engineering Cambridge, England}
}

@book{sutton1998introduction,
  title={Introduction to reinforcement learning},
  author={Sutton, Richard S and Barto, Andrew G and others},
  volume={135},
  year={1998},
  publisher={MIT press Cambridge}
}

@article{hernandez2019understanding,
  title={Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the {DQN} Target},
  author={Hernandez-Garcia, J Fernando and Sutton, Richard S},
  journal={arXiv preprint arXiv:1901.07510},
  year={2019}
}

@article{tieleman2012lecture,
  title={Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude},
  author={Tieleman, Tijmen and Hinton, Geoffrey},
  journal={COURSERA: Neural networks for machine learning},
  volume={4},
  number={2},
  pages={26--31},
  year={2012}
}

@article{moore1990efficient,
  title={Efficient memory-based learning for robot control},
  author={Moore, Andrew William},
  year={1990},
  publisher={Citeseer}
}

@article{brockman2016openai,
  title={Openai gym},
  author={Brockman, Greg and Cheung, Vicki and Pettersson, Ludwig and Schneider, Jonas and Schulman, John and Tang, Jie and Zaremba, Wojciech},
  journal={arXiv preprint arXiv:1606.01540},
  year={2016}
}


@techreport{lin1993reinforcement,
  title={Reinforcement learning for robots using neural networks},
  author={Lin, Long-Ji},
  year={1993},
  institution={Carnegie-Mellon Univ Pittsburgh PA School of Computer Science}
}

@article{singh2000convergence,
  title={Convergence results for single-step on-policy reinforcement-learning algorithms},
  author={Singh, Satinder and Jaakkola, Tommi and Littman, Michael L and Szepesv{\'a}ri, Csaba},
  journal={Machine learning},
  volume={38},
  number={3},
  pages={287--308},
  year={2000},
  publisher={Springer}
}

@article{lillicrap2015continuous,
  title={Continuous control with deep reinforcement learning},
  author={Lillicrap, Timothy P and Hunt, Jonathan J and Pritzel, Alexander and Heess, Nicolas and Erez, Tom and Tassa, Yuval and Silver, David and Wierstra, Daan},
  journal={arXiv preprint arXiv:1509.02971},
  year={2015}
}

@inproceedings{haarnoja2018soft,
  title={Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor},
  author={Haarnoja, Tuomas and Zhou, Aurick and Abbeel, Pieter and Levine, Sergey},
  booktitle={International Conference on Machine Learning},
  pages={1861--1870},
  year={2018},
  organization={PMLR}
}

@inproceedings{fujimoto2018addressing,
  title={Addressing function approximation error in actor-critic methods},
  author={Fujimoto, Scott and Hoof, Herke and Meger, David},
  booktitle={International Conference on Machine Learning},
  pages={1587--1596},
  year={2018},
  organization={PMLR}
}

@article{schulman2017proximal,
  title={Proximal policy optimization algorithms},
  author={Schulman, John and Wolski, Filip and Dhariwal, Prafulla and Radford, Alec and Klimov, Oleg},
  journal={arXiv preprint arXiv:1707.06347},
  year={2017}
}

@article{wang2016sample,
  title={Sample efficient actor-critic with experience replay},
  author={Wang, Ziyu and Bapst, Victor and Heess, Nicolas and Mnih, Volodymyr and Munos, Remi and Kavukcuoglu, Koray and de Freitas, Nando},
  journal={arXiv preprint arXiv:1611.01224},
  year={2016}
}

@article{schulman2015high,
  title={High-dimensional continuous control using generalized advantage estimation},
  author={Schulman, John and Moritz, Philipp and Levine, Sergey and Jordan, Michael and Abbeel, Pieter},
  journal={arXiv preprint arXiv:1506.02438},
  year={2015}
}

@inproceedings{schulman2015trust,
  title={Trust region policy optimization},
  author={Schulman, John and Levine, Sergey and Abbeel, Pieter and Jordan, Michael and Moritz, Philipp},
  booktitle={International conference on machine learning},
  pages={1889--1897},
  year={2015},
  organization={PMLR}
}


@inproceedings{mnih2016asynchronous,
  title={Asynchronous methods for deep reinforcement learning},
  author={Mnih, Volodymyr and Badia, Adria Puigdomenech and Mirza, Mehdi and Graves, Alex and Lillicrap, Timothy and Harley, Tim and Silver, David and Kavukcuoglu, Koray},
  booktitle={International conference on machine learning},
  pages={1928--1937},
  year={2016}
}

@inproceedings{bellemare2017distributional,
  title={A distributional perspective on reinforcement learning},
  author={Bellemare, Marc G and Dabney, Will and Munos, R{\'e}mi},
  booktitle={International Conference on Machine Learning},
  pages={449--458},
  year={2017},
  organization={PMLR}
}

@article{achiam2019towards,
  title={Towards Characterizing Divergence in Deep {Q}-Learning},
  author={Achiam, Joshua and Knight, Ethan and Abbeel, Pieter},
  journal={arXiv preprint arXiv:1903.08894},
  year={2019}
}

@article{tsitsiklis1997analysis,
  title={An analysis of temporal-difference learning with function approximation},
  author={Tsitsiklis, John N and Van Roy, Benjamin},
  journal={IEEE transactions on automatic control},
  volume={42},
  number={5},
  pages={674--690},
  year={1997},
  publisher={IEEE}
}

@article{tesauro1994td,
  title={TD-Gammon, a self-teaching backgammon program, achieves master-level play},
  author={Tesauro, Gerald},
  journal={Neural computation},
  volume={6},
  number={2},
  pages={215--219},
  year={1994},
  publisher={MIT Press}
}

@incollection{peng1994incremental,
  title={Incremental multi-step Q-learning},
  author={Peng, Jing and Williams, Ronald J},
  booktitle={Machine Learning Proceedings 1994},
  pages={226--232},
  year={1994},
  publisher={Elsevier}
}

@inproceedings{wiering1998speeding,
  title={Speeding up Q ($\lambda$)-learning},
  author={Wiering, Marco and Schmidhuber, J{\"u}rgen},
  booktitle={European Conference on Machine Learning},
  pages={352--363},
  year={1998},
  organization={Springer}
}

@article{geist2014off,
  title={Off-policy learning with eligibility traces: a survey.},
  author={Geist, Matthieu and Scherrer, Bruno and others},
  journal={J. Mach. Learn. Res.},
  volume={15},
  number={1},
  pages={289--333},
  year={2014}
}
@article{lin1992self,
  title={Self-improving reactive agents based on reinforcement learning, planning and teaching},
  author={Lin, Long-Ji},
  journal={Machine learning},
  volume={8},
  number={3-4},
  pages={293--321},
  year={1992},
  publisher={Springer}
}

@incollection{baird1995residual,
  title={Residual algorithms: Reinforcement learning with function approximation},
  author={Baird, Leemon},
  booktitle={Machine Learning Proceedings 1995},
  pages={30--37},
  year={1995},
  publisher={Elsevier}
}


@article{lazaric2007reinforcement,
  title={Reinforcement learning in continuous action spaces through sequential monte carlo methods},
  author={Lazaric, Alessandro and Restelli, Marcello and Bonarini, Andrea},
  journal={Advances in neural information processing systems},
  volume={20},
  pages={833--840},
  year={2007}
}

@article{jaakkola1995reinforcement,
  title={Reinforcement learning algorithm for partially observable Markov decision problems},
  author={Jaakkola, Tommi and Singh, Satinder P and Jordan, Michael I},
  journal={Advances in neural information processing systems},
  pages={345--352},
  year={1995},
  publisher={MORGAN KAUFMANN PUBLISHERS}
}

@article{arulkumaran2017deep,
  title={Deep reinforcement learning: A brief survey},
  author={Arulkumaran, Kai and Deisenroth, Marc Peter and Brundage, Miles and Bharath, Anil Anthony},
  journal={IEEE Signal Processing Magazine},
  volume={34},
  number={6},
  pages={26--38},
  year={2017},
  publisher={IEEE}
}

@techreport{sabatelli2017learning,
  title={Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks},
  author={Sabatelli, Matthia},
  year={2017},
  school={Faculty of Science and Engineering}
}

@inproceedings{lee2013bias,
  title={Bias-corrected q-learning to control max-operator bias in q-learning},
  author={Lee, Donghun and Defourny, Boris and Powell, Warren B},
  booktitle={2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL)},
  pages={93--99},
  year={2013},
  organization={IEEE}
}

@article{pentaliotis2021variation,
  title={Variation-resistant Q-learning: Controlling and Utilizing Estimation Bias in Reinforcement Learning for Better Performance},
  author={Pentaliotis, Andreas and Wiering, Marco},
  year={2021}
}

@article{kaiser2019model,
  title={Model-based reinforcement learning for atari},
  author={Kaiser, Lukasz and Babaeizadeh, Mohammad and Milos, Piotr and Osinski, Blazej and Campbell, Roy H and Czechowski, Konrad and Erhan, Dumitru and Finn, Chelsea and Kozakowski, Piotr and Levine, Sergey and others},
  journal={arXiv preprint arXiv:1903.00374},
  year={2019}
}

@article{obando2020revisiting,
  title={Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research},
  author={Obando-Ceron, Johan S and Castro, Pablo Samuel},
  journal={arXiv preprint arXiv:2011.14826},
  year={2020}
}

@article{zhu2020self,
  title={Self-correcting Q-Learning},
  author={Zhu, Rong and Rigotti, Mattia},
  journal={arXiv preprint arXiv:2012.01100},
  year={2020}
}

@article{lee2019bias,
  title={Bias-corrected Q-learning with multistate extension},
  author={Lee, Donghun and Powell, Warren B},
  journal={IEEE Transactions on Automatic Control},
  volume={64},
  number={10},
  pages={4011--4023},
  year={2019},
  publisher={IEEE}
}

@inproceedings{thrun1993issues,
  title={Issues in using function approximation for reinforcement learning},
  author={Thrun, Sebastian and Schwartz, Anton},
  booktitle={Proceedings of the Fourth Connectionist Models Summer School},
  pages={255--263},
  year={1993},
  organization={Hillsdale, NJ}
}

@article{lane1992theory,
  title={Theory and development of higher-order CMAC neural networks},
  author={Lane, Stephen H and Handelman, David A and Gelfand, Jack J},
  journal={IEEE Control Systems Magazine},
  volume={12},
  number={2},
  pages={23--30},
  year={1992},
  publisher={IEEE}
}

@inproceedings{wiering2004convergence,
  title={Convergence and divergence in standard and averaging reinforcement learning},
  author={Wiering, Marco A},
  booktitle={European Conference on Machine Learning},
  pages={477--488},
  year={2004},
  organization={Springer}
}

@article{park1993approximation,
  title={Approximation and radial-basis-function networks},
  author={Park, Jooyoung and Sandberg, Irwin W},
  journal={Neural computation},
  volume={5},
  number={2},
  pages={305--316},
  year={1993},
  publisher={MIT Press}
}

@article{an2018discrete,
  title={Discrete space reinforcement learning algorithm based on support vector machine classification},
  author={An, Yuexuan and Ding, Shifei and Shi, Songhui and Li, Jingcan},
  journal={Pattern Recognition Letters},
  volume={111},
  pages={30--35},
  year={2018},
  publisher={Elsevier}
}

@article{franccois2018introduction,
  title={An introduction to deep reinforcement learning},
  author={Fran{\c{c}}ois-Lavet, Vincent and Henderson, Peter and Islam, Riashat and Bellemare, Marc G and Pineau, Joelle},
  journal={arXiv preprint arXiv:1811.12560},
  year={2018}
}


@article{liu1998sequential,
  title={Sequential Monte Carlo methods for dynamic systems},
  author={Liu, Jun S and Chen, Rong},
  journal={Journal of the American statistical association},
  volume={93},
  number={443},
  pages={1032--1044},
  year={1998},
  publisher={Taylor \& Francis}
}