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Fairness risk measures

Fairness risk measures

24 January 2019
Robert C. Williamson
A. Menon
    FaML
ArXivPDFHTML

Papers citing "Fairness risk measures"

34 / 34 papers shown
Title
Federated Learning with Relative Fairness
Federated Learning with Relative Fairness
Shogo H. Nakakita
Tatsuya Kaneko
Shinya Takamaeda-Yamazaki
Masaaki Imaizumi
FedML
39
2
0
02 Nov 2024
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Quan Nguyen
Nishant A. Mehta
Cristóbal Guzmán
39
1
0
01 Oct 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Yuze Ge
Rujun Jiang
47
0
0
19 Jul 2024
Evaluating Model Performance Under Worst-case Subpopulations
Evaluating Model Performance Under Worst-case Subpopulations
Mike Li
Hongseok Namkoong
Shangzhou Xia
48
17
0
01 Jul 2024
Semi-Variance Reduction for Fair Federated Learning
Semi-Variance Reduction for Fair Federated Learning
Saber Malekmohammadi
Yaoliang Yu
FedML
80
1
0
23 Jun 2024
An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating
  Algorithm
An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm
Armando J. Cabrera Pacheco
Rabanus Derr
Robert C. Williamson
46
0
0
04 Jun 2024
AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark
AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark
Li Lin
Santosh
Xin Eric Wang
Shu Hu
Shu Hu
EGVM
86
11
0
02 Jun 2024
Fast Computation of Superquantile-Constrained Optimization Through
  Implicit Scenario Reduction
Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction
Jake Roth
Ying Cui
31
2
0
13 May 2024
Fairness Risks for Group-conditionally Missing Demographics
Fairness Risks for Group-conditionally Missing Demographics
Kaiqi Jiang
Wenzhe Fan
Mao Li
Xinhua Zhang
105
0
0
20 Feb 2024
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of
  Large Language Models
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models
Thomas P. Zollo
Todd Morrill
Zhun Deng
Jake C. Snell
T. Pitassi
Richard Zemel
45
8
0
22 Nov 2023
A Model-Based Method for Minimizing CVaR and Beyond
A Model-Based Method for Minimizing CVaR and Beyond
S. Meng
Robert Mansel Gower
26
4
0
27 May 2023
On the Richness of Calibration
On the Richness of Calibration
Benedikt Höltgen
Robert C. Williamson
13
9
0
08 Feb 2023
Stochastic Optimization for Spectral Risk Measures
Stochastic Optimization for Spectral Risk Measures
Ronak R. Mehta
Vincent Roulet
Krishna Pillutla
Lang Liu
Zaïd Harchaoui
42
6
0
10 Dec 2022
Malign Overfitting: Interpolation Can Provably Preclude Invariance
Malign Overfitting: Interpolation Can Provably Preclude Invariance
Yoav Wald
G. Yona
Uri Shalit
Y. Carmon
24
6
0
28 Nov 2022
Rank-based Decomposable Losses in Machine Learning: A Survey
Rank-based Decomposable Losses in Machine Learning: A Survey
Shu Hu
Xin Wang
Siwei Lyu
40
32
0
18 Jul 2022
(Im)possibility of Collective Intelligence
(Im)possibility of Collective Intelligence
Krikamol Muandet
40
6
0
05 Jun 2022
Optimizing generalized Gini indices for fairness in rankings
Optimizing generalized Gini indices for fairness in rankings
Virginie Do
Nicolas Usunier
15
29
0
02 Apr 2022
Exploring the Unfairness of DP-SGD Across Settings
Exploring the Unfairness of DP-SGD Across Settings
Frederik Noe
R. Herskind
Anders Søgaard
27
4
0
24 Feb 2022
Fair Wrapping for Black-box Predictions
Fair Wrapping for Black-box Predictions
Alexander Soen
Ibrahim M. Alabdulmohsin
Sanmi Koyejo
Yishay Mansour
Nyalleng Moorosi
Richard Nock
Ke Sun
Lexing Xie
FaML
53
6
0
31 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data
AutoBalance: Optimized Loss Functions for Imbalanced Data
Mingchen Li
Xuechen Zhang
Christos Thrampoulidis
Jiasi Chen
Samet Oymak
24
67
0
04 Jan 2022
A Survey of Learning Criteria Going Beyond the Usual Risk
A Survey of Learning Criteria Going Beyond the Usual Risk
Matthew J. Holland
Kazuki Tanabe
FaML
29
4
0
11 Oct 2021
Fairness Through Counterfactual Utilities
Fairness Through Counterfactual Utilities
Jack Blandin
Ian A. Kash
FaML
38
2
0
11 Aug 2021
Teacher's pet: understanding and mitigating biases in distillation
Teacher's pet: understanding and mitigating biases in distillation
Michal Lukasik
Srinadh Bhojanapalli
A. Menon
Sanjiv Kumar
18
25
0
19 Jun 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
36
94
0
02 Mar 2021
Achieving Efficiency in Black Box Simulation of Distribution Tails with
  Self-structuring Importance Samplers
Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers
Anand Deo
Karthyek Murthy
30
10
0
14 Feb 2021
Device Sampling for Heterogeneous Federated Learning: Theory,
  Algorithms, and Implementation
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
85
110
0
04 Jan 2021
Active Deep Learning on Entity Resolution by Risk Sampling
Active Deep Learning on Entity Resolution by Risk Sampling
Youcef Nafa
Qun Chen
Zhaoqiang Chen
Xingyu Lu
Haiyang He
Tianyi Duan
Zhanhuai Li
10
16
0
23 Dec 2020
Coping with Label Shift via Distributionally Robust Optimisation
Coping with Label Shift via Distributionally Robust Optimisation
J.N. Zhang
A. Menon
Andreas Veit
Srinadh Bhojanapalli
Sanjiv Kumar
S. Sra
OOD
24
70
0
23 Oct 2020
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic
  Multi-Objective Approach
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach
Suyun Liu
Luis Nunes Vicente
FaML
29
68
0
03 Aug 2020
Learning Bounds for Risk-sensitive Learning
Learning Bounds for Risk-sensitive Learning
Jaeho Lee
Sejun Park
Jinwoo Shin
25
46
0
15 Jun 2020
Projection to Fairness in Statistical Learning
Projection to Fairness in Statistical Learning
Thibaut Le Gouic
Jean-Michel Loubes
Philippe Rigollet
33
3
0
24 May 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
215
908
0
02 Mar 2020
Adaptive Sampling for Stochastic Risk-Averse Learning
Adaptive Sampling for Stochastic Risk-Averse Learning
Sebastian Curi
Kfir Y. Levy
Stefanie Jegelka
Andreas Krause
24
52
0
28 Oct 2019
Fairness Constraints: Mechanisms for Fair Classification
Fairness Constraints: Mechanisms for Fair Classification
Muhammad Bilal Zafar
Isabel Valera
Manuel Gomez Rodriguez
Krishna P. Gummadi
FaML
114
49
0
19 Jul 2015
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