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Censoring Representations with an Adversary

18 November 2015

Amos Storkey

Papers citing "Censoring Representations with an Adversary"

50 / 205 papers shown

Title
Are Commercial Face Detection Models as Biased as Academic Models? Samuel Dooley George Z. Wei Tom Goldstein John P. Dickerson CVBM 80 4 0 25 Jan 2022
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 79 36 0 04 Nov 2021
Algorithmic encoding of protected characteristics in image-based models for disease detection Ben Glocker Charles Jones Mélanie Bernhardt S. Winzeck 94 9 0 27 Oct 2021
Comparing Human and Machine Bias in Face Recognition Samuel Dooley Ryan Downing George Z. Wei N. Shankar Bradon Thymes ... Olufemi Obiwumi Valeriia Cherepanova Micah Goldblum John P. Dickerson Tom Goldstein CVBM 191 12 0 15 Oct 2021
Residual2Vec: Debiasing graph embedding with random graphs Sadamori Kojaku Jisung Yoon I. Constantino Yong-Yeol Ahn CML 78 23 0 14 Oct 2021
Convex-Concave Min-Max Stackelberg Games Denizalp Goktas Amy Greenwald 101 30 0 05 Oct 2021
Adversarial Representation Learning With Closed-Form Solvers Bashir Sadeghi Lan Wang Vishnu Boddeti 64 5 0 12 Sep 2021
On Characterizing the Trade-off in Invariant Representation Learning Bashir Sadeghi Sepehr Dehdashtian Vishnu Boddeti 105 7 0 08 Sep 2021
TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks Amirarsalan Rajabi O. Garibay GAN 82 58 0 02 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 83 20 0 01 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 168 536 0 31 Aug 2021
Adversarial Stacked Auto-Encoders for Fair Representation Learning Patrik Kenfack Adil Khan Rasheed Hussain S. M. Ahsan Kazmi FaML 29 4 0 27 Jul 2021
Impossibility results for fair representations Tosca Lechner Shai Ben-David Sushant Agarwal Nivasini Ananthakrishnan FaML 35 15 0 07 Jul 2021
Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation Pratik Mazumder Pravendra Singh Vinay P. Namboodiri SSL 43 2 0 30 Jun 2021
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis Xianjing Liu Yue Liu Esther E. Bron W. Niessen E. Wolvius Gennady Roshchupkin CVBM 87 10 0 25 Jun 2021
Fairness via Representation Neutralization Mengnan Du Subhabrata Mukherjee Guanchu Wang Ruixiang Tang Ahmed Hassan Awadallah Helen Zhou 90 81 0 23 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 57 38 0 10 Jun 2021
Fair Representations by Compression Xavier Gitiaux Huzefa Rangwala FaML 114 14 0 28 May 2021
Obstructing Classification via Projection P. Haghighatkhah Wouter Meulemans Bettina Speckmann Jérôme Urhausen Kevin Verbeek 49 6 0 19 May 2021
Improving Fairness of AI Systems with Lossless De-biasing Yan Zhou Murat Kantarcioglu Chris Clifton 66 12 0 10 May 2021
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features Tianxiang Zhao Enyan Dai Kai Shu Suhang Wang FaML 74 58 0 29 Apr 2021
Unsupervised Information Obfuscation for Split Inference of Neural Networks Mohammad Samragh H. Hosseini Aleksei Triastcyn K. Azarian Joseph B. Soriaga F. Koushanfar 59 11 0 23 Apr 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 90 25 0 24 Feb 2021
Technical Challenges for Training Fair Neural Networks Valeriia Cherepanova V. Nanda Micah Goldblum John P. Dickerson Tom Goldstein FaML 71 22 0 12 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 81 52 0 08 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 123 25 0 05 Feb 2021
Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling Chris Emmery Ákos Kádár Grzegorz Chrupała AAML 92 20 0 27 Jan 2021
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation Umang Gupta Aaron Ferber B. Dilkina Greg Ver Steeg 101 58 0 11 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 312 500 0 31 Dec 2020
Fundamental Limits and Tradeoffs in Invariant Representation Learning Han Zhao Chen Dan Bryon Aragam Tommi Jaakkola Geoffrey J. Gordon Pradeep Ravikumar FaML 96 45 0 19 Dec 2020
TARA: Training and Representation Alteration for AI Fairness and Domain Generalization William Paul Armin Hadzic Neil J. Joshi F. Alajaji Philippe Burlina 89 19 0 11 Dec 2020
FairOD: Fairness-aware Outlier Detection Shubhranshu Shekhar Neil Shah Leman Akoglu 70 37 0 05 Dec 2020
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks L. N. Darlow Stanisław Jastrzębski Amos Storkey 134 24 0 19 Nov 2020
Metric-Free Individual Fairness with Cooperative Contextual Bandits Qian Hu Huzefa Rangwala FaML 52 10 0 13 Nov 2020
All of the Fairness for Edge Prediction with Optimal Transport Charlotte Laclau I. Redko Manvi Choudhary C. Largeron FaML 61 43 0 30 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 121 48 0 19 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 70 385 0 14 Oct 2020
Measuring and Reducing Gendered Correlations in Pre-trained Models Kellie Webster Xuezhi Wang Ian Tenney Alex Beutel Emily Pitler Ellie Pavlick Jilin Chen Ed Chi Slav Petrov FaML 90 260 0 12 Oct 2020
FairMixRep : Self-supervised Robust Representation Learning for Heterogeneous Data with Fairness constraints Souradip Chakraborty Ekansh Verma Saswata Sahoo J. Datta 47 2 0 07 Oct 2020
Fairness Perception from a Network-Centric Perspective Farzan Masrour P. Tan A. Esfahanian FaML 37 2 0 07 Oct 2020
Can we Generalize and Distribute Private Representation Learning? Sheikh Shams Azam Taejin Kim Seyyedali Hosseinalipour Carlee Joe-Wong S. Bagchi Christopher G. Brinton 112 11 0 05 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 106 653 0 04 Oct 2020
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders Mo Han Ozan Özdenizci T. Koike-Akino Ye Wang Deniz Erdogmus OOD AAML DRL 68 10 0 28 Sep 2020
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach Cuong Tran Ferdinando Fioretto Pascal Van Hentenryck FedML 79 80 0 26 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 117 248 0 03 Sep 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 106 86 0 20 Aug 2020
Null-sampling for Interpretable and Fair Representations T. Kehrenberg Myles Bartlett Oliver Thomas Novi Quadrianto OOD 41 29 0 12 Aug 2020
$Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence$ Beyond $\mathcal{H}$ -Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence Changjian Shui Qi Chen Jun Wen Fan Zhou Christian Gagné Boyu Wang 97 23 0 30 Jul 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 126 58 0 29 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 70 62 0 18 Jul 2020