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@article{fair_washing,
title = {Fairwashing: the {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}}}
@inproceedings{amershi2015modeltracker,
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}}}
@article{angwin16,
Author = {Julia Angwin and Jeff Larson and Surya Mattu and Lauren Kirchner},
Journal = {ProPublica},
Title = {{M}achine {B}ias: {T}here's {S}oftware {U}sed {A}cross the {C}ountry to {P}redict {F}uture {C}riminals. {A}nd {I}t's {B}iased {A}gainst {B}lacks.},
note = {URL: \url{https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing}},
Year = {2016}}
@article{ale_plot,
title = {Visualizing the {E}ffects of {P}redictor {V}ariables in {B}lack {B}ox {S}upervised {L}earning {M}odels},
author = {Apley, Daniel W.},
journal = {arXiv preprint arXiv:1612.08468},
year = {2016},
note = {URL: \url{https://arxiv.org/pdf/1612.08468.pdf}}}
@book{barocas-hardt-narayanan,
title = {Fairness and Machine Learning},
author = {Solon Barocas and Moritz Hardt and Arvind Narayanan},
publisher = {fairmlbook.org},
note = {URL: \url{http://www.fairmlbook.org}},
year = {2018}}
@article{security_of_ml,
title={The {S}ecurity of {M}achine {L}earning},
author={Barreno, Marco and Nelson, Blaine and Joseph, Anthony D and Tygar, J Doug},
journal={Machine Learning},
volume={81},
number={2},
pages={121--148},
year={2010},
publisher={Springer},
note={URL: \url{https://people.eecs.berkeley.edu/~adj/publications/paper-files/SecML-MLJ2010.pdf}}}
@article{dt_surrogate2,
title = {Interpreting {B}lackbox {M}odels via {M}odel {E}xtraction},
author ={Osbert Bastani and Carolyn Kim and Hamsa Bastani},
journal = {arXiv preprint arXiv:1705.08504},
note = {URL: \url{https://arxiv.org/pdf/1705.08504.pdf}},
year = {2017}}
@inproceedings{viper,
title={Verifiable {R}einforcement {L}earning {V}ia {P}olicy {E}xtraction},
author={Bastani, Osbert and Pu, Yewen and Solar-Lezama, Armando},
booktitle={Advances in Neural Information Processing Systems},
pages={2494--2504},
year={2018},
note={URL: \url{http://papers.nips.cc/paper/7516-verifiable-reinforcement-learning-via-policy-extraction.pdf}}}
@article{calders2010three,
title={Three {N}a\"{i}ve {B}ayes {A}pproaches for {D}iscrimination-free {C}lassification},
author={Calders, Toon and Verwer, Sicco},
journal={Data Mining and Knowledge Discovery},
volume={21},
number={2},
pages={277--292},
year={2010},
publisher={Springer},
note={URL: \url{https://link.springer.com/content/pdf/10.1007/s10618-010-0190-x.pdf}}}
@inproceedings{calmon2017optimized,
title={Optimized {P}re-processing for {D}iscrimination {P}revention},
author={Calmon, Flavio and Wei, Dennis and Vinzamuri, Bhanukiran and Ramamurthy, Karthikeyan Natesan and Varshney, Kush R.},
booktitle={Advances in Neural Information Processing Systems},
pages={3992--4001},
year={2017},
note={URL: \url{http://papers.nips.cc/paper/6988-optimized-pre-processing-for-discrimination-prevention.pdf}}}
@article{dt_surrogate1,
Author = {Mark W. Craven and Jude W. Shavlik},
Journal = {Advances in Neural Information Processing Systems},
Title = {Extracting {T}ree-{S}tructured {R}epresentations of {T}rained {N}etworks},
note={URL: \url{http://papers.nips.cc/paper/1152-extracting-tree-structured-representations-of-trained-networks.pdf}},
Year = {1996}}
@inproceedings{feldman2015certifying,
title={Certifying and {R}emoving {D}isparate {I}mpact},
author={Feldman, Michael and Friedler, Sorelle A. and Moeller, John and Scheidegger, Carlos and Venkatasubramanian, Suresh},
booktitle={Proceedings of the 21\textsuperscript{st} ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages={259--268},
year={2015},
organization={ACM},
note={URL: \url{https://arxiv.org/pdf/1412.3756.pdf}}}
@article{been_kim1,
Author = {Finale Doshi-Velez and Been Kim},
Title = {Towards a {R}igorous {S}cience of {I}nterpretable {M}achine {L}earning},
Journal = {arXiv preprint arXiv:1702.08608},
note = {URL: \url{https://arxiv.org/pdf/1702.08608.pdf}},
Year = {2017}}
@article{flores2016false,
title={False {P}ositives, {F}alse {N}egatives, and {F}alse {A}nalyses: {A} {R}ejoinder to {M}achine {B}ias: {T}here's {S}oftware {U}sed across the {C}ountry to {P}redict {F}uture {C}riminals. {A}nd {I}t's {B}iased against {B}lacks},
author={Flores, Anthony W. and Bechtel, Kristin and Lowenkamp, Christopher T.},
journal={Fed. Probation},
volume={80},
pages={38},
year={2016},
publisher={HeinOnline},
note={URL: \url{https://bit.ly/2Gesf9Y}}}
@article{friedler2019assessing,
title={{A}ssessing the {L}ocal {I}nterpretability of {M}achine {L}earning {M}odels},
author={Friedler, Sorelle A. and Roy, Chitradeep Dutta and Scheidegger, Carlos and Slack, Dylan},
journal={arXiv preprint arXiv:1902.03501},
year={2019},
note={URL: \url{https://arxiv.org/pdf/1902.03501.pdf}}}
@book{esl,
Address = {New York},
Author = {Jerome Friedman and Trevor Hastie and Robert Tibshirani},
Booktitle = {\textit{The Elements of Statistical Learning}},
Publisher = {Springer},
Title = {\textbf{The Elements of Statistical Learning}},
note = {URL: \url{https://web.stanford.edu/~hastie/ElemStatLearn/printings/ESLII\_print12.pdf}},
Year = {2001}}
@inproceedings{hardt2016equality,
title={Equality of {O}pportunity in {S}upervised {L}earning},
author={Hardt, Moritz and Price, Eric and Srebro, Nati and others},
booktitle={Advances in neural information processing systems},
pages={3315--3323},
year={2016},
note={URL: \url{http://papers.nips.cc/paper/6374-equality-of-opportunity-in-supervised-learning.pdf}}}
@inproceedings{hcml,
title={Human-{C}entred {M}achine {L}earning},
author={Gillies, Marco and Fiebrink, Rebecca and Tanaka, Atau and Garcia, J{\'e}r{\'e}mie and Bevilacqua, Fr{\'e}d{\'e}ric and Heloir, Alexis and Nunnari, Fabrizio and Mackay, Wendy and Amershi, Saleema and Lee, Bongshin and others},
booktitle={Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems},
pages={3558--3565},
year={2016},
organization={ACM},
note={URL: \url{http://research.gold.ac.uk/16112/1/HCML2016.pdf}}}
@article{gilpin2018explaining,
title = {Explaining {E}xplanations: {A}n {A}pproach to {E}valuating {I}nterpretability of {M}achine {L}earning},
author = {Leilani H. Gilpin and David Bau and Ben Z. Yuan and Ayesha Bajwa and Michael Specter and Lalana Kagal},
journal = {arXiv preprint arXiv:1806.00069},
note = {URL: \url{https://arxiv.org/pdf/1806.00069.pdf}},
year = {2018}}
@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}}}
@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://link.springer.com/content/pdf/10.1007/s10115-011-0463-8.pdf}}}
@misc{gopinathan1998fraud,
title = {Fraud {D}etection using {P}redictive {M}odeling},
author = {Gopinathan, Krishna M. and Biafore, Louis S. and Ferguson, William M. and Lazarus, Michael A. and Pathria, Anu K. and Jost, Allen},
year = {1998},
month = oct # "~6",
publisher = {Google Patents},
note = {US Patent 5,819,226. URL: \url{https://patents.google.com/patent/US5819226A}}}
@article{gosiewska2019safe,
title={S{A}{F}{E} {M}{L}: {S}urrogate {A}ssisted {F}eature {E}xtraction for {M}odel {L}earning},
author={Gosiewska, Alicja and Gacek, Aleksandra and Lubon, Piotr and Biecek, Przemyslaw},
journal={arXiv preprint arXiv:1902.11035},
year={2019},
note={URL: \url{https://arxiv.org/pdf/1902.11035v1.pdf}}}
@article{guidotti2018survey,
title = {{A} {S}urvey of {M}ethods for {E}xplaining {B}lack {B}ox {M}odels},
author = {Guidotti, Riccardo and Monreale, Anna and Ruggieri, Salvatore and Turini, Franco and Giannotti, Fosca and Pedreschi, Dino},
journal = {ACM Computing Surveys (CSUR)},
volume = {51},
number = {5},
pages = {93},
year = {2018},
publisher = {ACM},
note = {URL: \url{https://arxiv.org/pdf/1802.01933.pdf}}}
@inproceedings{art_and_sci,
title = {On the {A}rt and {S}cience of {M}achine {L}earning {E}xplanations},
author = {Hall, Patrick},
booktitle={JSM Proceedings, Statistical Computing Section},
pages = {1781--1799},
publisher = {American Statistical Association},
note = {URL: \url{https://github.com/jphall663/jsm_2018_paper}},
year = {2018}}
@inproceedings{hardt2016equality,
title={Equality of {O}pportunity in {S}upervised {L}earning},
author={Hardt, Moritz and Price, Eric and Srebro, Nati and others},
booktitle={Advances in Neural Information Processing Systems},
pages={3315--3323},
year={2016},
note={URL: \url{http://papers.nips.cc/paper/6374-equality-of-opportunity-in-supervised-learning.pdf}}}
@article{lime-sup,
title = {Locally {I}nterpretable {M}odels and {E}ffects {B}ased on {S}upervised {P}artitioning ({LIME-SUP})},
author = {Linwei Hu and Jie Chen and Vijayan N. Nair and Agus Sudjianto},
journal = {arXiv preprint arXiv:1806.00663},
note = {URL: \url{https://arxiv.org/ftp/arxiv/papers/1806/1806.00663.pdf}},
year = {2018}}
@misc{kangdebugging,
title={Debugging {M}achine {L}earning {M}odels via {M}odel {A}ssertions},
author={Kang, Daniel and Raghavan, Deepti and Bailis, Peter and Zaharia, Matei},
note={URL: \url{https://debug-ml-iclr2019.github.io/cameraready/DebugML-19_paper_27.pdf}}}
@article{keinan2004fair,
title = {Fair {A}ttribution of {F}unctional {C}ontribution in {A}rtificial and {B}iological {N}etworks},
author = {Keinan, Alon and Sandbank, Ben and Hilgetag, Claus C. and Meilijson, Isaac and Ruppin, Eytan},
journal = {Neural Computation},
volume = {16},
number = {9},
pages = {1887--1915},
year = {2004},
publisher = {MIT Press},
note={URL: \url{http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.436.6801&rep=rep1&type=pdf}}}
@misc{uci,
author = {M. Lichman},
year = {2013},
title = {{UCI} {M}achine {L}earning {R}epository},
note = {URL: \url{http://archive.ics.uci.edu/ml}},
institution = {University of California, Irvine, School of Information and Computer Sciences"}}
@article{lipovetsky2001analysis,
title={Analysis of {R}egression in {G}ame {T}heory {A}pproach},
author={Lipovetsky, Stan and Conklin, Michael},
journal={Applied Stochastic Models in Business and Industry},
volume={17},
number={4},
pages={319--330},
year={2001},
publisher={Wiley Online Library}}
@article{lipton1,
title = {The {M}ythos of {M}odel {I}nterpretability},
author = {Lipton, Zachary C.},
journal = {arXiv preprint arXiv:1606.03490},
year = {2016},
note = {URL: \url{https://arxiv.org/pdf/1606.03490.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 30},
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{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{molnar2019quantifying,
title={Quantifying {I}nterpretability of {A}rbitrary {M}achine {L}earning {M}odels {T}hrough {F}unctional {D}ecomposition},
author={Molnar, Christoph and Casalicchio, Giuseppe and Bischl, Bernd},
journal={arXiv preprint arXiv:1904.03867},
year={2019},
note={URL: \url{https://arxiv.org/pdf/1904.03867.pdf}}}
@article{murdoch2019interpretable,
title={Interpretable {M}achine {L}earning: {D}efinitions, {M}ethods, and {A}pplications},
author={Murdoch, W. James and Singh, Chandan and Kumbier, Karl and Abbasi-Asl, Reza and Yu, Bin},
journal={arXiv preprint arXiv:1901.04592},
year={2019},
note={URL: \url{https://arxiv.org/pdf/1901.04592.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}}}
@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{lime,
title = {Why {S}hould {I} {T}rust {Y}ou?: {E}xplaining the {P}redictions of {A}ny {C}lassifier},
author = {Marco Tulio Ribeiro and Sameer Singh and Carlos Guestrin},
booktitle = {Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages = {1135--1144},
year = {2016},
note = {URL: \url{http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf}},
organization = {ACM}}
@article{please_stop,
title = {Please {S}top {E}xplaining {B}lack {B}ox {M}odels for {H}igh {S}takes {D}ecisions},
author = {Rudin, Cynthia},
note = {URL: \url{https://arxiv.org/pdf/1811.10154.pdf}},
journal = {arXiv preprint arXiv:1811.10154},
year = {2018}}
@book{shapley1988shapley,
title = {\textit{The Shapley value: {E}ssays in honor of {L}loyd {S}. {S}hapley}},
author = {Shapley, Lloyd S. and Roth, Alvin E. and others},
year = {1988},
publisher = {Cambridge University Press},
note = {URL: \url{http://www.library.fa.ru/files/Roth2.pdf}}}
@inproceedings{membership_inference,
title={Membership {I}nference {A}ttacks {A}gainst {M}achine {L}earning {M}odels},
author={Shokri, Reza and Stronati, Marco and Song, Congzheng and Shmatikov, Vitaly},
booktitle={2017 IEEE Symposium on Security and Privacy (SP)},
pages={3--18},
year={2017},
organization={IEEE},
note={URL: \url{https://arxiv.org/pdf/1610.05820.pdf}}}
@article{shokri2019privacy,
title={Privacy {R}isks of {E}xplaining {M}achine {L}earning {M}odels},
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}}}
@article{kononenko2010efficient,
title = {An {E}fficient {E}xplanation of {I}ndividual {C}lassifications using {G}ame {T}heory},
author = {Strumbelj, Erik and Kononenko, Igor},
journal = {Journal of Machine Learning Research},
volume = {11},
number = {Jan},
pages = {1--18},
year = {2010},
note = {URL: \url{http://www.jmlr.org/papers/volume11/strumbelj10a/strumbelj10a.pdf}}}
@inproceedings{model_stealing,
title={Stealing {M}achine {L}earning {M}odels via {P}rediction {A}{P}{I}s},
author={Tram{\`e}r, Florian and Zhang, Fan and Juels, Ari and Reiter, Michael K and Ristenpart, Thomas},
booktitle={25th $\{$USENIX$\}$ Security Symposium ($\{$USENIX$\}$ Security 16)},
pages={601--618},
year={2016},
note={URL: \url{https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_tramer.pdf}}}
@article{slim,
Author = {Ustun, Berk and Rudin, Cynthia},
Journal = {Machine Learning},
Number = {3},
Pages = {349--391},
Publisher = {Springer},
Title = {{Supersparse {L}inear {I}nteger {M}odels for {O}ptimized {M}edical {S}coring {S}ystems}},
Volume = {102},
note={URL: \url{https://users.cs.duke.edu/~cynthia/docs/UstunTrRuAAAI13.pdf}},
Year = {2016}}
@article{wf_xnn,
title = {Explainable {N}eural {N}etworks {B}ased on {A}dditive {I}ndex {M}odels},
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