FORML: Learning to Reweight Data for Fairness

FORML: Learning to Reweight Data for Fairness

3 February 2022

Papers citing "FORML: Learning to Reweight Data for Fairness"

17 / 17 papers shown

Title
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 48 65 0 27 Oct 2021
Learning Soft Labels via Meta Learning Nidhi Vyas Shreyas Saxena T. Voice NoLa 70 30 0 20 Sep 2020
Fairness without Demographics through Adversarially Reweighted Learning Preethi Lahoti Alex Beutel Jilin Chen Kang Lee Flavien Prost Nithum Thain Xuezhi Wang Ed H. Chi FaML 111 335 0 23 Jun 2020
Identifying Mislabeled Data using the Area Under the Margin Ranking Geoff Pleiss Tianyi Zhang Ethan R. Elenberg Kilian Q. Weinberger NoLa 86 272 0 28 Jan 2020
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 107 733 0 12 Dec 2018
Learning to Teach with Dynamic Loss Functions Lijun Wu Fei Tian Yingce Xia Yang Fan Tao Qin Jianhuang Lai Tie-Yan Liu 68 112 0 29 Oct 2018
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter Heinrich Jiang S. Wang Taman Narayan Maya R. Gupta Seungil You Karthik Sridharan 74 155 0 11 Sep 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 143 1,426 0 24 Mar 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 227 2,232 0 08 Mar 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 95 1,452 0 14 Dec 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 823 11,899 0 09 Mar 2017
A General and Adaptive Robust Loss Function Jonathan T. Barron OOD DRL 185 538 0 11 Jan 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 297 2,110 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 222 4,307 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 114 1,769 0 19 Sep 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 105 2,006 0 14 Jun 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 429 18,350 0 27 May 2016