The Variational Fair Autoencoder

3 November 2015

Papers citing "The Variational Fair Autoencoder"

50 / 153 papers shown

Title
Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders J. Yan Xianyang Zhang 52 17 0 31 Dec 2021
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 36 19 0 26 Nov 2021
Learning Conditional Invariance through Cycle Consistency M. Samarin V. Nesterov Mario Wieser Aleksander Wieczorek S. Parbhoo Volker Roth 41 3 0 25 Nov 2021
Learning Domain Invariant Representations in Goal-conditioned Block MDPs Beining Han Chongyi Zheng Harris Chan Keiran Paster Michael Ruogu Zhang Jimmy Ba OOD AI4CE 20 13 0 27 Oct 2021
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models Yunhan Zheng Shenhao Wang Jinhuan Zhao HAI 24 27 0 25 Sep 2021
Fairness-aware Class Imbalanced Learning Shivashankar Subramanian Afshin Rahimi Timothy Baldwin Trevor Cohn Lea Frermann FaML 109 28 0 21 Sep 2021
Adversarial Representation Learning With Closed-Form Solvers Bashir Sadeghi Lan Wang Vishnu Boddeti 37 5 0 12 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 37 20 0 01 Sep 2021
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning Sen Cui Weishen Pan Jian Liang Changshui Zhang Fei Wang FedML 20 84 0 19 Aug 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 31 118 0 11 Aug 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 49 17 0 30 Jun 2021
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis Xianjing Liu Bo-wen Li Esther E. Bron W. Niessen E. Wolvius Gennady Roshchupkin CVBM 32 9 0 25 Jun 2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik Léon Bottou FaML 45 19 0 17 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 22 36 0 10 Jun 2021
An Information-theoretic Approach to Distribution Shifts Marco Federici Ryota Tomioka Patrick Forré OOD 44 17 0 07 Jun 2021
Fair Representations by Compression Xavier Gitiaux Huzefa Rangwala FaML 30 14 0 28 May 2021
Fair Feature Distillation for Visual Recognition S. Jung Donggyu Lee Taeeon Park Taesup Moon 27 75 0 27 May 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty Zehao Xiao Jiayi Shen Xiantong Zhen Ling Shao Cees G. M. Snoek BDL UQCV OOD 29 39 0 09 May 2021
AI Fairness via Domain Adaptation Neil J. Joshi Philippe Burlina 29 15 0 15 Mar 2021
Fair Mixup: Fairness via Interpolation Ching-Yao Chuang Youssef Mroueh 21 138 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 30 6 0 06 Mar 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 27 25 0 24 Feb 2021
Learning Invariant Representations using Inverse Contrastive Loss A. K. Akash Vishnu Suresh Lokhande Sathya Ravi Vikas Singh SSL 21 8 0 16 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification Maliha Tashfia Islam Anna Fariha A. Meliou Babak Salimi FaML 30 25 0 18 Jan 2021
Multi-type Disentanglement without Adversarial Training Lei Sha Thomas Lukasiewicz DRL 49 12 0 16 Dec 2020
Improving the Fairness of Deep Generative Models without Retraining Shuhan Tan Yujun Shen Bolei Zhou 183 59 0 09 Dec 2020
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations H. Feng Kezhi Kong Minghao Chen Tianye Zhang Minfeng Zhu Wei Chen VLM DRL 42 24 0 21 Nov 2020
Fairness in Biometrics: a figure of merit to assess biometric verification systems Tiago de Freitas Pereira S´ebastien Marcel 24 62 0 04 Nov 2020
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martínez Martín Bertrán Guillermo Sapiro FaML 25 188 0 03 Nov 2020
THIN: THrowable Information Networks and Application for Facial Expression Recognition In The Wild Estèphe Arnaud Arnaud Dapogny Kévin Bailly CVBM 29 23 0 15 Oct 2020
Tackling unsupervised multi-source domain adaptation with optimism and consistency Diogo Pernes Jaime S. Cardoso 29 8 0 29 Sep 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 29 49 0 25 Sep 2020
Attribute Privacy: Framework and Mechanisms Wanrong Zhang O. Ohrimenko Rachel Cummings 18 36 0 08 Sep 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 16 241 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 24 84 0 20 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 38 22 0 30 Jul 2020
Fairness-Aware Online Personalization G. R. Lal S. Geyik K. Kenthapadi FaML 8 3 0 30 Jul 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen R. Pfohl Agata Foryciarz N. Shah FaML 33 108 0 20 Jul 2020
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations Zhun Deng Frances Ding Cynthia Dwork Rachel Hong Giovanni Parmigiani Prasad Patil Pragya Sur OOD FaML 19 29 0 20 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 16 57 0 18 Jun 2020
PERL: Pivot-based Domain Adaptation for Pre-trained Deep Contextualized Embedding Models Eyal Ben-David Carmel Rabinovitz Roi Reichart SSL 58 61 0 16 Jun 2020
Disentanglement for Discriminative Visual Recognition Xiaofeng Liu DRL 27 6 0 14 Jun 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 19 25 0 11 Jun 2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning Pieter Delobelle Paul Temple Gilles Perrouin Benoit Frénay P. Heymans Bettina Berendt AAML FaML 24 14 0 14 May 2020
Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders Saeid Asgari Taghanaki Mohammad Havaei Alex Lamb Aditya Sanghi Aram Danielyan Tonya Custis DRL 38 7 0 12 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 43 371 0 30 Apr 2020
Fairness by Learning Orthogonal Disentangled Representations Mhd Hasan Sarhan Nassir Navab Abouzar Eslami Shadi Albarqouni FaML OOD CML 19 96 0 12 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020