Learning Adversarially Fair and Transferable Representations

17 February 2018

Papers citing "Learning Adversarially Fair and Transferable Representations"

50 / 108 papers shown

Title
Group-Aware Threshold Adaptation for Fair Classification T. Jang P. Shi Xiaoqian Wang FaML 78 36 0 08 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 19 36 0 04 Nov 2021
On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services Eren Kurshan Jiahao Chen Victor Storchan Hongda Shen FaML AIFin 19 9 0 02 Nov 2021
Algorithmic encoding of protected characteristics in image-based models for disease detection Ben Glocker Charles Jones Mélanie Bernhardt S. Winzeck 21 9 0 27 Oct 2021
Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models Yunhan Zheng Shenhao Wang Jinhuan Zhao HAI 16 27 0 25 Sep 2021
MPC-Friendly Commitments for Publicly Verifiable Covert Security Nitin Agrawal James Bell Adria Gascon Matt J. Kusner 18 4 0 15 Sep 2021
Adversarial Representation Learning With Closed-Form Solvers Bashir Sadeghi Lan Wang Vishnu Naresh Boddeti 29 5 0 12 Sep 2021
Fairness without the sensitive attribute via Causal Variational Autoencoder Vincent Grari Sylvain Lamprier Marcin Detyniecki 19 26 0 10 Sep 2021
Attributing Fair Decisions with Attention Interventions Ninareh Mehrabi Umang Gupta Fred Morstatter Greg Ver Steeg Aram Galstyan 24 21 0 08 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 24 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 29 515 0 31 Aug 2021
Federated Learning Meets Fairness and Differential Privacy P. Manisha Sankarshan Damle Sujit Gujar FedML 22 21 0 23 Aug 2021
Improving Counterfactual Generation for Fair Hate Speech Detection Aida Mostafazadeh Davani Ali Omrani Brendan Kennedy M. Atari Xiang Ren Morteza Dehghani 22 9 0 03 Aug 2021
Impossibility results for fair representations Tosca Lechner Shai Ben-David Sushant Agarwal Nivasini Ananthakrishnan FaML 11 13 0 07 Jul 2021
Fairness for Image Generation with Uncertain Sensitive Attributes A. Jalal Sushrut Karmalkar Jessica Hoffmann A. Dimakis Eric Price DiffM 27 39 0 23 Jun 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization Problems Babak Barazandeh Tianjian Huang George Michailidis 17 12 0 10 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 11 36 0 10 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 19 46 0 04 Jun 2021
Fair Representations by Compression Xavier Gitiaux Huzefa Rangwala FaML 17 14 0 28 May 2021
Towards Equity and Algorithmic Fairness in Student Grade Prediction Weijie Jiang Z. Pardos FaML 21 47 0 14 May 2021
Improving Fairness of AI Systems with Lossless De-biasing Yan Zhou Murat Kantarcioglu Chris Clifton 17 12 0 10 May 2021
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers Navid Rekabsaz Simone Kopeinik Markus Schedl 12 61 0 28 Apr 2021
Fair Mixup: Fairness via Interpolation Ching-Yao Chuang Youssef Mroueh 21 137 0 11 Mar 2021
Fairness in TabNet Model by Disentangled Representation for the Prediction of Hospital No-Show Sabri Boughorbel Fethi Jarray A. Kadri OOD 17 6 0 06 Mar 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 11 25 0 24 Feb 2021
Conditional Generation of Medical Images via Disentangled Adversarial Inference Mohammad Havaei Ximeng Mao Yiping Wang Qicheng Lao GAN MedIm 16 20 0 08 Dec 2020
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness Tong Wang M. Saar-Tsechansky 13 11 0 17 Nov 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 11 109 0 07 Nov 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 19 48 0 19 Oct 2020
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination Tao Zhang Tianqing Zhu Jing Li Mengde Han Wanlei Zhou Philip S. Yu FaML 16 49 0 25 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 11 239 0 03 Sep 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 8 58 0 29 Jul 2020
Same-Day Delivery with Fairness Xinwei Chen Tong Wang Barrett W. Thomas M. Ulmer 35 27 0 19 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 18 61 0 18 Jul 2020
Two Simple Ways to Learn Individual Fairness Metrics from Data Debarghya Mukherjee Mikhail Yurochkin Moulinath Banerjee Yuekai Sun FaML 21 96 0 19 Jun 2020
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances Meisam Razaviyayn Tianjian Huang Songtao Lu Maher Nouiehed Maziar Sanjabi Mingyi Hong 19 108 0 15 Jun 2020
On Disentangled Representations Learned From Correlated Data Frederik Trauble Elliot Creager Niki Kilbertus Francesco Locatello Andrea Dittadi Anirudh Goyal Bernhard Schölkopf Stefan Bauer OOD CML 16 115 0 14 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 13 38 0 26 May 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness Samuel Yeom Matt Fredrikson AAML 6 26 0 18 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 22 387 0 21 Jan 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 26 817 0 20 Jan 2020
Leveraging Semi-Supervised Learning for Fairness using Neural Networks Vahid Noroozi S. Bahaadini Samira Sheikhi Nooshin Mojab Philip S. Yu 8 7 0 31 Dec 2019
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation Zeyu Wang Klint Qinami Yannis Karakozis Kyle Genova P. Nair Kenji Hata Olga Russakovsky 27 354 0 26 Nov 2019
Auditing and Achieving Intersectional Fairness in Classification Problems Giulio Morina V. Oliinyk J. Waton Ines Marusic K. Georgatzis FaML 6 39 0 04 Nov 2019
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data Dylan Slack Sorelle A. Friedler Emile Givental FaML 21 54 0 24 Aug 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 18 19 0 25 Jun 2019
Incorporating Priors with Feature Attribution on Text Classification Frederick Liu Besim Avci FAtt FaML 23 120 0 19 Jun 2019
Learning Fair Representations via an Adversarial Framework Rui Feng Yang Yang Yuehan Lyu Chenhao Tan Yizhou Sun Chunping Wang FaML 11 55 0 30 Apr 2019
Large-Scale Long-Tailed Recognition in an Open World Ziwei Liu Zhongqi Miao Xiaohang Zhan Jiayun Wang Boqing Gong Stella X. Yu 17 1,131 0 10 Apr 2019