Reading group about Machine Learning topics at DFKI
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
.gitignore
README.md

README.md

Reading Group @ DFKI-SDS

Reading group about Machine Learning topics at DFKI

Guidelines:

  • You don't need faculty.
  • Be fearless. Ask dumb questions.
  • Choose your own papers to present.
  • It is better to show a PDF of a paper up on a projector, than to cancel a meeting.
  • After a major conference, have all of the people who attended the conference present their "top K papers."
  • If you need inspiration regarding a paper to present, have a look at the top papers on ArXiv Sanity Preserver.
  • If you can, please upload in advance the name of the paper you're presenting. This way, other people could prepare if they wish.
  • Meetings on Raskin, Tuesdays@11:00 (Booked until June 10 2018)

Participants:

  • FR: Federico Raue
  • SP: Sebastian Palacio
  • TK: Tushar Karayil
  • PB: Philipp Blandfort
  • BB: Benjamin Bischke
  • AG: Andrey Guzhov
  • SE: Sara Elkasrawi
  • PH: Patrick Helber
  • FA: Fatemeh Azimi
  • NB: Naseer Bajwa
  • YT: YouTube

Former members

  • MS: Marco Schreyer
  • VC: Victor Campos
  • WT: William Thong
  • MM: Mohsin Munir
  • TR: Tahseen Rizvi

Meetings:

Date Paper Speaker
26.07.2016 Ngiam et al. "Multimodal Deep Learning." ICML 2011. FR
02.08.2016 Du Tran et al. "Learning Spatiotemporal Features with 3D Convolutional Networks" CoRR 2014. SP
16.08.2016 Goodfellow et al. "Generative Adversarial Nets" NIPS 2014. TK
23.08.2016 Jaderberg et al. "Spatial transformer networks" NIPS 2015. source code (torch) VC
30.08.2016 Makhzani et al. "Adversarial Autoencoders" CoRR 2015. PB
06.09.2016 Yixuan Li et al. "Convergent Learning: Do different neural networks learn the same representations?" ICLR 2016. SP
20.09.2016 van den Oord et al. "Pixel Recurrent Neural Networks" CoRR 2016 TK
27.09.2016 Krueger et al. "Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations" CoRR 2016. FR
04.10.2016 Weston et al. "Memory Networks" ICLR 2015. PB
11.10.2016 Abu-El-Haija, S. et al. "YouTube-8M: A Large-Scale Video Classification Benchmark" 2016 SP
25.10.2016 Srivastava et al. "Training Very Deep Networks" NIPS 2015 "Project Website" FR
8.11.2016 Greff, K. et al. "Highway and Residual Networks learn Unrolled Iterative Estimation" Submitted to ICLR 2017 TK
14.11.2016 Radford, A. et al. "Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks" CoRR 2016 FR
22.11.2016 Tran, D. et al. "ViCom: Benchmark and Methods for Video Comprehension" CoRR 2016 SP
29.11.2016 * tumbleweed * -
24.01.2017 "Nuts and Bolts of Applying Deep Learning" by Andrew Ng (Part 1/2) -
31.01.2017 "Nuts and Bolts of Applying Deep Learning" by Andrew Ng (Part 2/2) -
7.02.2017 Dumoulin, V. et al. "Adversarially Learned Inference" ICLR2017 FR
14.02.2017 Marino, K. et al. "The More You Know: Using Knowledge Graphs for Image Classification" CoRR 12.2016 SP
21.02.2017 None None
28.02.2017 Schmidhuber, J. "Learning Factorial Codes by Predictability Minimization". Neural Computation 1992. TK
11.04.2017 Diederik P Kingma, Max Welling "Auto-Encoding Variational Bayes". ICLR 2014 BB
21.04.2017 Hendricks, L. A. et al. "Generating Visual Explanations". ECCV 2016. PB
21.04.2017 Kirkpatrick, J. et al. "Overcoming catastrophic forgetting in neural networks". PNAS 2017 MS
02.05.2017 (Short) Introduction to Reinforcement Learning FR
09.05.2017 (Short) Introduction to Fisher Information and Reimann Manifolds :- Intro to Fisher Information TK
16.05.2017 Yisheng, L. et al. "Traffic Flow Prediction With Big Data: A Deep Learning Approach". IEEE Transactions on Intelligent Transportation Systems 2015. MM
26.05.2017 Jifeng Dai. et al. "Deformable Convolutional Networks". 22.03.2017 BB
31.05.2017 Han Zhang. et al. "StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks". 10.12.2016 TR
06.06.2017 Junyoung Chung et al. "A Recurrent Latent Variable Model for Sequential Data". NIPS 2015 PB
13.06.2017 Chiyuan Zhang et al. "Understanding deep learning requires rethinking generalization". ICLR 2017 SP
27.06.2017 Alexander Pritzel et al. "Neural Episodic Control". 06.03.2017 MS
18.07.2017 Kaiming He et al. "Deep Residual Learning for Image Recognition". 10.12.2015 MM
25.07.2017 Xiangyu Zhang. et al. "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices". TR
08.08.2017 He et al. "An Unsupervised Neural Attention Model for Aspect Extraction". ACL 2017 PB
15.08.2017 Villegas et al. "Learning to Generate Long-term Future via Hierarchical Prediction". ICML 2017 SP
22.08.2017 Chen and Zaki "KATE: K-Competitive Autoencoder for Text". KDD 2017 MS
29.08.2017 Samuel Albanie. et al. "Stopping GAN Violence: Generative Unadversarial Networks". TR
10.10.2017 Tom Hope et al. "Accelerating Innovation Through Analogy Mining". KDD 2017 MM
07.11.2017 Gregoire Montavon et al. "Explaining Nonlinear Classification Decisions with Deep Taylor Decomposition". Pattern Recognition 2017 PB
21.11.2017 Author et al. "Network Dissection: Quantifying Interpretability of Deep Visual Representations". CVPR 2017 BB
28.11.2017 Author et al. "One model to learn them all". CoRR 2017 SP
05.12.2017 Yang, F. et al. "Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features". EMNLP 2017 SE
16.01.2018 John Platt "Energy Strategies to Decrease CO2 Emissions". NIPS 2017 --
16.01.2018 Ali Rahimi "Let's take machine learning from alchemy to electricity". NIPS 2017 --
23.01.2018 Michael Figurnov et al. "Spatially Adaptive Computation Time for Residual Networks". CVPR 2017 PH
06.02.2018 Ethics in Machine Learning. See e.g. IEEE Code of Ethics. PB
13.02.2018 Yang et al. "Towards K-Means-Friendly Spaces: Simultaneous Deep Learning and Clustering". ICML 2017 MS
20.02.2018 Mnih et al. "Playing Atari with Deep Reinforcement Learning". 2013 FA
27.02.2018 Li et al. "Generative Moment Matching Networks". ICML 2015 BB
06.03.2018 Avi and Larochelle "Optimization as a Model for Few-Shot Learning". ICLR 2017 FR
13.03.2018 Guo et al. "CCountering Adversarial Images using Input Transformations". ICLR 2018 SP
20.03.2018 Pelt and Sethian ["A mixed-scale dense convolutional neural network for image analysis"] (http://www.pnas.org/content/115/2/254). PNAS 2018 NB
10.04.2018 Xia et al. "Deliberation Networks: Sequence Generation Beyond One-Pass Decoding". NIPS 2017 SE
17.04.2018 Volokitin, Anna, Gemma Roig, and Tomaso A. Poggio. "Do Deep Neural Networks Suffer from Crowding?." Advances in Neural Information Processing Systems. 201 TK
22.05.2018 Neil C. Rabinowitz et al. "Machine Theory of Mind". CoRR 2018 BB
05.06.2018 Greff K. et al. "Neural Expectation Maximization". NIPS 2017 PH
12.06.2018 YouTube et al. "ICLR oral taks". ICLR 2018 YT
03.07.2018 Overview and impressions of CVPR 2018 SP
10.07.2018 Zamir et al. "Taskonomy: Disentangling Task Transfer Learning". Project Website (Best Paper Award) CVPR 2018 FR
17.07.2018 Vladlen Koltun "Doing (Good) Research". CVPR Workshop 2018 YT
24.07.2018 Liang et al. "Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection". CVPR 2017 FA
31.07.2018 Bojanowski et al. "Unsupervised Learning by Predicting Noise". ICML2017 FR
16.10.2018 ECCV2018 overview FA
dd.mm.yyyy xx_et al._ "paper". conference year ??