Adversarial Stacked Auto-Encoders for Fair Representation Learning

Adversarial Stacked Auto-Encoders for Fair Representation Learning

27 July 2021

Rasheed Hussain

S. M. Ahsan Kazmi

Papers citing "Adversarial Stacked Auto-Encoders for Fair Representation Learning"

12 / 12 papers shown

Title
On the Fairness of Generative Adversarial Networks (GANs) Patrik Kenfack Daniil Dmitrievich Arapovy Rasheed Hussain S. M. Ahsan Kazmi A. Khan GAN 30 21 0 01 Mar 2021
Anomaly Detection based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation Adín Ramirez Rivera A. Khan I. E. I. Bekkouch T. S. Sheikh 36 39 0 10 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 472 4,285 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 301 678 0 17 Feb 2018
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations Alex Beutel Jilin Chen Zhe Zhao Ed H. Chi FaML 66 442 0 01 Jul 2017
Multimodal Machine Learning: A Survey and Taxonomy T. Baltrušaitis Chaitanya Ahuja Louis-Philippe Morency 60 2,890 0 26 May 2017
Stacked Generative Adversarial Networks Xun Huang Yixuan Li Omid Poursaeed John E. Hopcroft Serge J. Belongie GAN 51 459 0 13 Dec 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 91 4,276 0 07 Oct 2016
Censoring Representations with an Adversary Harrison Edwards Amos Storkey AAML FaML 41 504 0 18 Nov 2015
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 116 633 0 03 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 535 149,474 0 22 Dec 2014
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 134 12,384 0 24 Jun 2012

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.