The Variational Fair Autoencoder

3 November 2015

Papers citing "The Variational Fair Autoencoder"

50 / 154 papers shown

Title
MADAN: Multi-source Adversarial Domain Aggregation Network for Domain Adaptation Sicheng Zhao Bo-wen Li Xiangyu Yue Pengfei Xu Kurt Keutzer OOD 46 64 0 19 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 386 0 21 Jan 2020
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits Han Guo Ramakanth Pasunuru Joey Tianyi Zhou 30 114 0 13 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
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks Nina Miolane Frédéric Poitevin Yee-Ting Li S. Holmes 3DV 16 23 0 19 Nov 2019
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare Natalia Martínez Martín Bertrán Guillermo Sapiro 11 25 0 16 Nov 2019
Multi-source Domain Adaptation for Semantic Segmentation Sicheng Zhao Bo-wen Li Xiangyu Yue Yang Gu Pengfei Xu Runbo Hu Hua Chai Kurt Keutzer 32 159 0 27 Oct 2019
Fair Generative Modeling via Weak Supervision Kristy Choi Aditya Grover Trisha Singh Rui Shu Stefano Ermon 36 133 0 26 Oct 2019
On the Global Optima of Kernelized Adversarial Representation Learning Bashir Sadeghi Runyi Yu Vishnu Boddeti AAML 67 31 0 16 Oct 2019
Conditional Learning of Fair Representations Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 22 106 0 16 Oct 2019
Conditional out-of-sample generation for unpaired data using trVAE M. Lotfollahi Mohsen Naghipourfar Fabian J. Theis F. A. Wolf GAN ViT DRL 22 19 0 04 Oct 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 341 4,230 0 23 Aug 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 33 173 0 28 Jul 2019
Rényi Fair Inference Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 24 66 0 28 Jun 2019
Learning Fair Representations for Kernel Models Zilong Tan Samuel Yeom Matt Fredrikson Ameet Talwalkar FaML 27 25 0 27 Jun 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 37 19 0 25 Jun 2019
Transfer of Machine Learning Fairness across Domains Candice Schumann Xuezhi Wang Alex Beutel Jilin Chen Hai Qian Ed H. Chi 35 69 0 24 Jun 2019
Fair Division Without Disparate Impact A. Peysakhovich Christian Kroer 30 10 0 06 Jun 2019
Does Object Recognition Work for Everyone? Terrance Devries Ishan Misra Changhan Wang Laurens van der Maaten 45 262 0 06 Jun 2019
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis Cynthia Rudin David Carlson HAI 30 34 0 04 Jun 2019
DualDis: Dual-Branch Disentangling with Adversarial Learning Thomas Robert Nicolas Thome Matthieu Cord CoGe DRL 30 4 0 03 Jun 2019
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination Nathan Kallus Xiaojie Mao Angela Zhou FaML 24 155 0 01 Jun 2019
Overlearning Reveals Sensitive Attributes Congzheng Song Vitaly Shmatikov 19 148 0 28 May 2019
DIVA: Domain Invariant Variational Autoencoders Maximilian Ilse Jakub M. Tomczak Christos Louizos Max Welling DRL OOD 33 198 0 24 May 2019
Fairness in Recommendation Ranking through Pairwise Comparisons Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Li Wei ... Lukasz Heldt Zhe Zhao Lichan Hong Ed H. Chi Cristos Goodrow FaML 36 373 0 02 Mar 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 30 150 0 14 Jan 2019
Unsupervised learning with contrastive latent variable models Kristen A. Severson S. Ghosh Kenney Ng SSL DRL 27 38 0 14 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 34 618 0 02 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 33 166 0 01 Nov 2018
Counterfactual Fairness in Text Classification through Robustness Sahaj Garg Vincent Perot Nicole Limtiaco Ankur Taly Ed H. Chi Alex Beutel 22 258 0 27 Sep 2018
Adversarial Removal of Demographic Attributes from Text Data Yanai Elazar Yoav Goldberg FaML 13 304 0 20 Aug 2018
Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia P. Gyawali B. Horácek J. Sapp Linwei Wang 38 3 0 04 Aug 2018
Hierarchical VampPrior Variational Fair Auto-Encoder P. Botros Jakub M. Tomczak DRL 15 7 0 26 Jun 2018
What About Applied Fairness? Jared Sylvester Edward Raff FaML 14 10 0 13 Jun 2018
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making Preethi Lahoti Krishna P. Gummadi Gerhard Weikum FaML 20 166 0 04 Jun 2018
FairGAN: Fairness-aware Generative Adversarial Networks Depeng Xu Shuhan Yuan Lu Zhang Xintao Wu GAN 33 306 0 28 May 2018
Invariant Representations without Adversarial Training Daniel Moyer Shuyang Gao Rob Brekelmans Greg Ver Steeg Aram Galstyan OOD 15 208 0 24 May 2018
A Universal Music Translation Network Noam Mor Lior Wolf Adam Polyak Yaniv Taigman 25 110 0 21 May 2018
Causal Reasoning for Algorithmic Fairness Joshua R. Loftus Chris Russell Matt J. Kusner Ricardo M. A. Silva FaML CML 18 125 0 15 May 2018
Unsupervised Domain Adaptation with Adversarial Residual Transform Networks Guanyu Cai Yuqin Wang Mengchu Zhou Lianghua He GAN 19 88 0 25 Apr 2018
Strong Baselines for Neural Semi-supervised Learning under Domain Shift Sebastian Ruder Barbara Plank 17 171 0 25 Apr 2018
Graphite: Iterative Generative Modeling of Graphs Aditya Grover Aaron Zweig Stefano Ermon BDL 33 296 0 28 Mar 2018
Learning from Noisy Web Data with Category-level Supervision Li Niu Qingtao Tang Ashok Veeraraghavan A. Sabharwal NoLa 30 32 0 10 Mar 2018
Path-Specific Counterfactual Fairness Silvia Chiappa Thomas P. S. Gillam CML FaML 40 334 0 22 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 675 0 17 Feb 2018
Fairness in Supervised Learning: An Information Theoretic Approach AmirEmad Ghassami S. Khodadadian Negar Kiyavash FaML 9 48 0 13 Jan 2018
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations Alex Beutel Jilin Chen Zhe Zhao Ed H. Chi FaML 19 441 0 01 Jul 2017
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 69 731 0 24 May 2017
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 20 1,558 0 20 Mar 2017
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning Werner Zellinger Thomas Grubinger E. Lughofer T. Natschläger Susanne Saminger-Platz OOD 21 563 0 28 Feb 2017