article-information-2019.bib.bak

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 	author={Rudin, Cynthia},
	note={URL: \url{https://arxiv.org/pdf/1811.10154.pdf}},
	journal={arXiv preprint arXiv:1811.10154},
	year={2018}}

@inproceedings{feldman2015certifying,
	title={Certifying and {R}emoving {D}isparate {I}mpact},
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	pages={259--268},
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	note={URL: \url{https://arxiv.org/pdf/1412.3756.pdf}}}

@inproceedings{dwork2012fairness,
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	pages={214--226},
	year={2012},
	organization={ACM},
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@inproceedings{gender_shades,
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	pages={77--91},
	year={2018},
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@article{security_of_ml,
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@inproceedings{model_stealing,
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@inproceedings{membership_inference,
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 	pages={3--18},
 	year={2017},
 	organization={IEEE},
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@article{shokri2019privacy,
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	author={Shokri, Reza and Strobel, Martin and Zick, Yair},
	journal={arXiv preprint arXiv:1907.00164},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1907.00164.pdf}}}

@book{ff_interpretability,
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@incollection{friedman1979tree,
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@article{friedman1991multivariate,
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@misc{hmda,
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  note={Accessed: 2020-02-24}}

@article{friedman2001greedy,
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@book{esl,
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	Year={2001}}

@inproceedings{recht2011hogwild,
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@article{hinton2012improving,
	title={Improving {N}eural {N}etworks by {P}reventing {C}o-adaptation of {F}eature {D}etectors},
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	journal={arXiv preprint arXiv:1207.0580},
	year={2012},
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@inproceedings{sutskever2013importance,
	title={On the {I}mportance of {I}nitialization and {M}omentum in {D}eep {L}earning},
	author={Sutskever, Ilya and Martens, James and Dahl, George and Hinton, Geoffrey},
	booktitle={International Conference on Machine Learning},
	pages={1139--1147},
	year={2013},
	note={URL: \url{http://proceedings.mlr.press/v28/sutskever13.pdf}}}

@article{zeiler2012adadelta,
	title={{A}{D}{A}{D}{E}{L}{T}{A}: {A}n {A}daptive {L}earning {R}ate {M}ethod},
	author={Zeiler, Matthew D.},
	journal={arXiv preprint arXiv:1212.5701},
	year={2012},
	note={URL: \url{https://arxiv.org/pdf/1212.5701.pdf}}}

@article{fair_washing,
	title={Fairwashing: {T}he {R}isk of {R}ationalization},
	author={A{\"\i}vodji, Ulrich and Arai, Hiromi and Fortineau, Olivier and Gambs, S{\'e}bastien and Hara, Satoshi and Tapp, Alain},
	journal={arXiv preprint arXiv:1901.09749},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1901.09749.pdf}}}

@article{scaffolding,
	title={{F}ooling {L}{I}{M}{E} and {S}{H}{A}{P}: {A}dversarial {A}ttacks on {P}ost-hoc {E}xplanation {M}ethods},
	author={Dylan Slack and Sophie Hilgard and Emily Jia and Sameer Singh and Himabindu Lakkaraju},
	journal={arXiv preprint arXiv:1911.02508},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1911.02508.pdf}}}

@article{wf_xnn,
	title={Explainable {N}eural {N}etworks {B}ased on {A}dditive {I}ndex {M}odels},
	author={Vaughan, Joel and Sudjianto, Agus and Brahimi, Erind and Chen, Jie and Nair, Vijayan N.},
	journal={arXiv preprint arXiv:1806.01933},
	note={URL: \url{https://arxiv.org/pdf/1806.01933.pdf}},
	year={2018}}

@article{yang2019enhancing,
	title={Enhancing {E}xplainability of {N}eural {N}etworks {T}hrough {A}rchitecture {C}onstraints},
	author={Yang, Zebin and Zhang, Aijun and Sudjianto, Agus},
	journal={arXiv preprint arXiv:1901.03838},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1901.03838.pdf}}}

@article{ice_plots,
	Author={Alex Goldstein and Adam Kapelner and Justin Bleich and Emil Pitkin},
	Journal={Journal of Computational and Graphical Statistics},
	Number={1},
	Title={Peeking {I}nside the {B}lack {B}ox: {V}isualizing {S}tatistical {L}earning with {P}lots of {I}ndividual {C}onditional {E}xpectation},
	Volume={24},
	Year={2015},
	note={URL: \url{https://arxiv.org/pdf/1309.6392.pdf}}}

@incollection{shapley,
	title={A {U}nified {A}pproach to {I}nterpreting {M}odel {P}redictions},
	author={Lundberg, Scott M. and Lee, Su-In},
	booktitle={Advances in Neural Information Processing Systems (NIPS)},
	editor={I. Guyon and U. V. Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
	pages={4765--4774},
	year={2017},
	publisher={Curran Associates, Inc.},
	note={URL: \url{http://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions.pdf}}}

@incollection{tree_shap,
	title={Consistent {I}ndividualized {F}eature {A}ttribution for {T}ree {E}nsembles},
	author={Lundberg, Scott M. and Erion, Gabriel G. and Lee, Su-In},
	booktitle={Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017)},
	pages={15--21},
	editor={Been Kim and Dmitry M. Malioutov and Kush R. Varshney and Adrian Weller},
	year={2017},
	note={URL: \url{https://openreview.net/pdf?id=ByTKSo-m-}},
	publisher={ICML WHI 2017},
	organization={ICML}}

@book{cohen1988statistical,
	title={\textbf{Statistical {P}ower {A}nalysis for the {B}ehavioral {S}ciences}},
	author={Cohen, Jacob},
	year={1988},
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@article{cohen1992power,
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@inproceedings{zafar2017fairness,
	title={Fairness {B}eyond {D}isparate {T}reatment \& {D}isparate {I}mpact: {L}earning {C}lassification {W}ithout {D}isparate {M}istreatment},
	author={Zafar, Muhammad Bilal and Valera, Isabel and Gomez Rodriguez, Manuel and Gummadi, Krishna P.},
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	pages={1171--1180},
	year={2017},
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	note={URL: \url{https://arxiv.org/pdf/1610.08452.pdf}}}

@inproceedings{ga2m,
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	author={Lou, Yin and Caruana, Rich and Gehrke, Johannes and Hooker, Giles},
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@article{ale_plot,
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 	journal={arXiv preprint arXiv:1612.08468},
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	note={URL: \url{https://arxiv.org/pdf/1612.08468.pdf}}}

@book{shapley1988shapley,
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@inproceedings{art_and_sci,
	title={On the {A}rt and {S}cience of {M}achine {L}earning {E}xplanations},
	author={Hall, Patrick},
	booktitle={KDD '19 XAI Workshop},
	note={URL: \url{https://arxiv.org/pdf/1810.02909.pdf}},
	year={2019}}

@book{molnar,
	title={\textbf{\textit{{I}nterpretable {M}achine {L}earning}}},
	author={Christoph Molnar},
	publisher={christophm.github.io},
	note={URL: \url{https://christophm.github.io/interpretable-ml-book/}},
	year={2018}}

@article{osdt,
	title={Optimal {S}parse {D}ecision {T}rees},
	author={Hu, Xiyang and Rudin, Cynthia and Seltzer, Margo},
	journal={arXiv preprint arXiv:1904.12847},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1904.12847.pdf}}}

@article{rulefit,
	title={Predictive {L}earning {V}ia {R}ule {E}nsembles},
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@article{lattice,
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	author={Gupta, Maya and Cotter, Andrew and Pfeifer, Jan and Voevodski, Konstantin and Canini, Kevin and Mangylov, Alexander and Moczydlowski, Wojciech and Van Esbroeck, Alexander},
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	year={2016},
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@inproceedings{this_looks_like_that,
	title={{T}his {L}ooks {L}ike {T}hat: {D}eep {L}earning for {I}nterpretable {I}mage {R}ecognition},
	author={Chaofan Chen and Oscar Li and Alina Barnett and Jonathan Su and Cynthia Rudin},
	booktitle={Proceedings of Neural Information Processing Systems {(NeurIPS)}},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1806.10574.pdf}}}

@article{wilkinson2018visualizing,
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	author={Wilkinson, Leland},
	journal={IEEE Transactions on Visualization \& Computer Graphics},
	year={2018},
	publisher={IEEE},
	note={URL: \url{https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf}}}

@article{udell2016generalized,
	title={Generalized {L}ow {R}ank {M}odels},
	author={Udell, Madeleine and Horn, Corinne and Zadeh, Reza and Boyd, Stephen and others},
	journal={Foundations and Trends{\textregistered} in Machine Learning},
	volume={9},
	number={1},
	pages={1--118},
	year={2016},
	publisher={Now Publishers, Inc.},
	note={URL: \url{https://www.nowpublishers.com/article/Details/MAL-055}}}

@article{diffprivlib,
	title={{D}iffprivlib: {T}he {I}{B}{M} {D}ifferential {P}rivacy {L}ibrary},
	author={Holohan, Naoise and Braghin, Stefano and Mac Aonghusa, P{\'o}l and Levacher, Killian},
	journal={arXiv preprint arXiv:1907.02444},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1907.02444.pdf}}}

@article{ji2014differential,
	title={Differential {P}rivacy and {M}achine {L}earning: {A} {S}urvey and {R}eview},
	author={Ji, Zhanglong and Lipton, Zachary C. and Elkan, Charles},
	journal={arXiv preprint arXiv:1412.7584},
	year={2014},
	note={URL: \url{https://arxiv.org/pdf/1412.7584.pdf}}}

@article{pate,
	title={Scalable {P}rivate {L}earning with {P}{A}{T}{E}},
	author={Papernot, Nicolas and Song, Shuang and Mironov, Ilya and Raghunathan, Ananth and Talwar, Kunal and Erlingsson, {\'U}lfar},
	journal={arXiv preprint arXiv:1802.08908},
	year={2018},
	note={URL: \url{https://arxiv.org/pdf/1802.08908.pdf}}}

@inproceedings{abadi2016deep,
	title={Deep {L}earning with {D}ifferential {P}rivacy},
	author={Abadi, Martin and Chu, Andy and Goodfellow, Ian and McMahan, H Brendan and Mironov, Ilya and Talwar, Kunal and Zhang, Li},
	booktitle={Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security},
	pages={308--318},
	year={2016},
	organization={ACM},
	note={URL: \url{https://arxiv.org/pdf/1607.00133.pdf}}}

@book{book_of_why,
  title={The {B}ook of {W}hy: {T}he {N}ew {S}cience of {C}ause and {E}ffect},
  author={Pearl, Judea and Mackenzie, Dana},
  year={2018},
  publisher={Basic Books},
  note={URL: \url{http://cdar.berkeley.edu/wp-content/uploads/2017/04/Lisa-Goldberg-reviews-The-Book-of-Why.pdf}}
}

@article{wachter2017counterfactual,
	title={Counterfactual {E}xplanations without {O}pening the {B}lack {B}ox: {A}utomated {D}ecisions and the {G}{P}{D}{R}},
	author={Wachter, Sandra and Mittelstadt, Brent and Russell, Chris},
	journal={Harv. JL \& Tech.},
	volume={31},
	pages={841},
	year={2017},
	publisher={HeinOnline},
	note={URL: \url{https://arxiv.org/pdf/1711.00399.pdf}}}

@inproceedings{grad_attr,
 	title={Towards {B}etter {U}nderstanding of {G}radient-based {A}ttribution {M}ethods for {D}eep {N}eural {N}etworks},
 	author={Ancona, Marco and Ceolini, Enea and Oztireli, Cengiz and Gross, Markus},
 	booktitle={6th International Conference on Learning Representations (ICLR 2018)},
 	note={URL: \url{https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/249929/Flow_ICLR_2018.pdf}},
 	year={2018}}

@article{wallace2019allennlp,
	title={AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models},
	author={Wallace, Eric and Tuyls, Jens and Wang, Junlin and Subramanian, Sanjay and Gardner, Matt and Singh, Sameer},
	journal={arXiv preprint arXiv:1909.09251},
	year={2019},
	note={URL: \url{https://arxiv.org/pdf/1909.09251.pdf}}}

@article{kamiran2012data,
	title={Data {P}reprocessing {T}echniques for {C}lassification {W}ithout {D}iscrimination},
	author={Kamiran, Faisal and Calders, Toon},
	journal={Knowledge and Information Systems},
	volume={33},
	number={1},
	pages={1--33},
	year={2012},
	publisher={Springer},
	note={URL: \url{https://bit.ly/2lH95lQ}}}

@inproceedings{zhang2018mitigating,
	title={Mitigating {U}nwanted {B}iases with {A}dversarial {L}earning},
	author={Zhang, Brian Hu and Lemoine, Blake and Mitchell, Margaret},
	booktitle={Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society},
	pages={335--340},
	year={2018},
	organization={ACM},
	note={URL: \url{https://arxiv.org/pdf/1801.07593.pdf}}}

@inproceedings{lfr,
	title={Learning {F}air {R}epresentations},
	author={Zemel, Rich and Wu, Yu and Swersky, Kevin and Pitassi, Toni and Dwork, Cynthia},
	booktitle={International Conference on Machine Learning},
	pages={325--333},
	year={2013},
	note={URL: \url{http://proceedings.mlr.press/v28/zemel13.pdf}}}

@inproceedings{kamiran2012decision,
	title={Decision {T}heory for {D}iscrimination-aware {C}lassification},
	author={Kamiran, Faisal and Karim, Asim and Zhang, Xiangliang},
	booktitle={2012 IEEE 12th International Conference on Data Mining},
	pages={924--929},
	year={2012},
	organization={IEEE},
	note={URL: \url{http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.722.3030&rep=rep1&type=pdf}}}

@article{rauber2017foolbox,
	title={{F}oolbox: {A} {P}ython {T}oolbox to {B}enchmark the {R}obustness of {M}achine {L}earning {M}odels},
	author={Rauber, Jonas and Brendel, Wieland and Bethge, Matthias},
	journal={arXiv preprint arXiv:1707.04131},
	year={2017},
	note={URL: \url{https://arxiv.org/pdf/1707.04131.pdf}}}

@article{papernot2018cleverhans,
	title={{T}echnical {R}eport on the {C}leverHans v2.1.0 {A}dversarial {E}xamples {L}ibrary},
	author={Nicolas Papernot and Fartash Faghri and Nicholas Carlini and
	Ian Goodfellow and Reuben Feinman and Alexey Kurakin and Cihang Xie and
	Yash Sharma and Tom Brown and Aurko Roy and Alexander Matyasko and
	Vahid Behzadan and Karen Hambardzumyan and Zhishuai Zhang and
	Yi-Lin Juang and Zhi Li and Ryan Sheatsley and Abhibhav Garg and
	Jonathan Uesato and Willi Gierke and Yinpeng Dong and David Berthelot and
	Paul Hendricks and Jonas Rauber and Rujun Long},
	journal={arXiv preprint arXiv:1610.00768},
	year={2018},
	note={URL: \url{https://arxiv.org/pdf/1610.00768.pdf}}}

@inproceedings{modeltracker,
	title={Modeltracker: {R}edesigning {P}erformance {A}nalysis {T}ools for {M}achine {L}earning},
	author={Amershi, Saleema and Chickering, Max and Drucker, Steven M. and Lee, Bongshin and Simard, Patrice and Suh, Jina},
 	booktitle={Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems},
 	pages={337--346},
 	year={2015},
 	organization={ACM},
	note={URL: \url{https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/amershi.CHI2015.ModelTracker.pdf}}}

@inproceedings{papernot2018marauder,
	title={A {M}arauder's {M}ap of {S}ecurity and {P}rivacy in {M}achine {L}earning: {A}n overview of current and future research directions for making machine learning secure and private},
	author={Papernot, Nicolas},
	booktitle={Proceedings of the 11th ACM Workshop on Artificial Intelligence and Security},
	year={2018},
	organization={ACM},
	note={URL: \url{https://arxiv.org/pdf/1811.01134.pdf}}}

@inproceedings{model_cards,
	title={Model {C}ards for {M}odel {R}eporting},
 	author={Mitchell, Margaret and Wu, Simone and Zaldivar, Andrew and Barnes, Parker and Vasserman, Lucy and Hutchinson, Ben and Spitzer, Elena and Raji, Inioluwa Deborah and Gebru, Timnit},
 	booktitle={Proceedings of the Conference on Fairness, Accountability, and Transparency},
 	pages={220--229},
 	year={2019},
 	organization={ACM},
	note={URL: \url{https://arxiv.org/pdf/1810.03993.pdf}}}


@article{bracke2019machine,
	title={Machine {L}earning {E}xplainability in {F}inance: {A}n {A}pplication to {D}efault {R}isk {A}nalysis},
	author={Bracke, Philippe and Datta, Anupam and Jung, Carsten and Sen, Shayak},
	year={2019},
	publisher={Bank of England Working Paper},
	note={URL: \url{https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2019/machine-learning-explainability-in-finance-an-application-to-default-risk-analysis.pdf}}}

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