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Censoring Representations with an Adversary

18 November 2015

Amos Storkey

Papers citing "Censoring Representations with an Adversary"

50 / 308 papers shown

Title
Adversarial Deep Learning in EEG Biometrics Ozan Özdenizci Ye Wang T. Koike-Akino Deniz Erdogmus 127 90 0 27 Mar 2019
Fairness in Recommendation Ranking through Pairwise ComparisonsKnowledge Discovery and Data Mining (KDD), 2019 Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Li Wei ... Lukasz Heldt Zhe Zhao Lichan Hong Ed H. Chi Cristos Goodrow FaML 212 411 0 02 Mar 2019
Adversarial Training for Satire Detection: Controlling for Confounding VariablesNorth American Chapter of the Association for Computational Linguistics (NAACL), 2019 R. McHardy Heike Adel Roman Klinger 172 32 0 28 Feb 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 244 369 0 21 Feb 2019
Fairness in representation: quantifying stereotyping as a representational harm Mohsen Abbasi Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian 170 53 0 28 Jan 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 277 310 0 15 Jan 2019
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Allison Woodruff Christine Luu Pierre Kreitmann Jonathan Bischof Ed H. Chi FaML 204 164 0 14 Jan 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 179 75 0 08 Jan 2019
Application-driven Privacy-preserving Data Publishing with Correlated Attributes A. Rezaei Chaowei Xiao Zhi-Xuan Liu Yue Liu Sirajum Munir 88 14 0 26 Dec 2018
Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders Ozan Özdenizci Ye Wang T. Koike-Akino Deniz Erdogmus OOD DRL 100 63 0 17 Dec 2018
Learning Latent Subspaces in Variational Autoencoders Jack Klys Jake C. Snell R. Zemel SSL DRL 195 146 0 14 Dec 2018
Learning Controllable Fair Representations Jiaming Song Pratyusha Kalluri Aditya Grover Shengjia Zhao Stefano Ermon FaML 208 183 0 11 Dec 2018
State of the Art in Fair ML: From Moral Philosophy and Legislation to Fair Classifiers Elias Baumann J. L. Rumberger FaML 123 4 0 20 Nov 2018
FNNC: Achieving Fairness through Neural Networks P. Manisha Sujit Gujar 382 78 0 01 Nov 2018
Mobile Sensor Data Anonymization Mohammad Malekzadeh R. Clegg Andrea Cavallaro Hamed Haddadi 330 246 0 26 Oct 2018
The Frontiers of Fairness in Machine Learning Alexandra Chouldechova Aaron Roth FaML 296 434 0 20 Oct 2018
Discovering Fair Representations in the Data Domain Novi Quadrianto V. Sharmanska Oliver Thomas 148 3 0 15 Oct 2018
Adversarial Recommendation: Attack of the Learned Fake Users Konstantina Christakopoulou A. Banerjee AAML 111 12 0 21 Sep 2018
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk Stephen Pfohl Ben J. Marafino Adrien Coulet F. Rodriguez L. Palaniappan N. Shah 159 74 0 12 Sep 2018
Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts Samuel Carton Qiaozhu Mei Paul Resnick FAtt AAML 245 34 0 01 Sep 2018
Adversarial Removal of Demographic Attributes from Text Data Yanai Elazar Yoav Goldberg FaML 446 323 0 20 Aug 2018
Deconfounding age effects with fair representation learning when assessing dementia Zining Zhu Jekaterina Novikova Frank Rudzicz 131 3 0 19 Jul 2018
Generative Adversarial Privacy Chong Huang Peter Kairouz Xiao Chen Lalitha Sankar Ram Rajagopal PICV 223 43 0 13 Jul 2018
Gradient Reversal Against DiscriminationInternational Conference on Data Science and Advanced Analytics (DSAA), 2018 Edward Raff Jared Sylvester 102 43 0 01 Jul 2018
What About Applied Fairness? Jared Sylvester Edward Raff FaML 171 11 0 13 Jun 2018
Causal Interventions for Fairness Matt J. Kusner Chris Russell Joshua R. Loftus Ricardo M. A. Silva FaML 206 15 0 06 Jun 2018
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making Preethi Lahoti Krishna P. Gummadi Gerhard Weikum FaML 143 182 0 04 Jun 2018
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning Jihun Hamm Yung-Kyun Noh 149 9 0 29 May 2018
FairGAN: Fairness-aware Generative Adversarial Networks Depeng Xu Shuhan Yuan Lu Zhang Xintao Wu GAN 214 343 0 28 May 2018
Fairness GAN P. Sattigeri Samuel C. Hoffman Vijil Chenthamarakshan Kush R. Varshney 180 92 0 24 May 2018
Invariant Representations from Adversarially Censored Autoencoders Ye Wang T. Koike-Akino Deniz Erdogmus CML 112 21 0 21 May 2018
Causal Reasoning for Algorithmic Fairness Joshua R. Loftus Chris Russell Matt J. Kusner Ricardo M. A. Silva FaML CML 164 137 0 15 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 457 1,632 0 10 May 2018
Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders A. Jha Saket Anand Maneesh Kumar Singh V. Veeravasarapu CoGe DRL 120 135 0 27 Apr 2018
Path-Specific Counterfactual Fairness Silvia Chiappa Thomas P. S. Gillam CML FaML 289 367 0 22 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 790 731 0 17 Feb 2018
Learning Privacy Preserving Encodings through Adversarial Training Francesco Pittaluga S. Koppal Ayan Chakrabarti PICV 303 78 0 14 Feb 2018
Fairness in Supervised Learning: An Information Theoretic Approach AmirEmad Ghassami S. Khodadadian Negar Kiyavash FaML 122 49 0 13 Jan 2018
Fair Forests: Regularized Tree Induction to Minimize Model BiasAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2017 Edward Raff Jared Sylvester S. Mills FaML 131 75 0 21 Dec 2017
Privacy-Preserving Adversarial NetworksAllerton Conference on Communication, Control, and Computing (Allerton), 2017 Ardhendu Shekhar Tripathy Ye Wang Prakash Ishwar PICV 177 87 0 19 Dec 2017
Multi-View Data Generation Without View Supervision Mickaël Chen Ludovic Denoyer Thierry Artières SyDa 183 19 0 01 Nov 2017
Context-Aware Generative Adversarial Privacy Chong Huang Peter Kairouz Xiao Chen Lalitha Sankar Ram Rajagopal 250 163 0 26 Oct 2017
Provably Fair Representations D. McNamara Cheng Soon Ong Robert C. Williamson FaML 149 57 0 12 Oct 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 365 946 0 06 Sep 2017
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses Ryan J. Lowe Michael Noseworthy Iulian Serban Nicolas Angelard-Gontier Yoshua Bengio Joelle Pineau 187 379 0 23 Aug 2017
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations Alex Beutel Jilin Chen Zhe Zhao Ed H. Chi FaML 280 462 0 01 Jul 2017
Avoiding Discrimination through Causal ReasoningNeural Information Processing Systems (NeurIPS), 2017 Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf FaML CML 321 617 0 08 Jun 2017
Fader Networks: Manipulating Images by Sliding AttributesNeural Information Processing Systems (NeurIPS), 2017 Guillaume Lample Neil Zeghidour Nicolas Usunier Antoine Bordes Ludovic Denoyer MarcÁurelio Ranzato DRL GAN 311 556 0 01 Jun 2017
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations Diane Bouchacourt Ryota Tomioka Sebastian Nowozin BDL OOD DRL 265 327 0 24 May 2017
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems Jure Sokolić Qiang Qiu M. Rodrigues Guillermo Sapiro FedML 78 5 0 23 May 2017