ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.06879
  4. Cited By
Active Sampling for Min-Max Fairness
v1v2v3 (latest)

Active Sampling for Min-Max Fairness

11 June 2020
Jacob D. Abernethy
Pranjal Awasthi
Matthäus Kleindessner
Jamie Morgenstern
Chris Russell
Jie Zhang
    FaML
ArXiv (abs)PDFHTML

Papers citing "Active Sampling for Min-Max Fairness"

24 / 24 papers shown
Title
Active Data Sampling and Generation for Bias Remediation
Active Data Sampling and Generation for Bias Remediation
Antonio Maratea
Rita Perna
136
0
0
26 Mar 2025
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Xuanqian Wang
Jing Li
Ivor Tsang
Yew-Soon Ong
76
1
0
04 Nov 2024
Adjusting Pretrained Backbones for Performativity
Adjusting Pretrained Backbones for Performativity
Berker Demirel
Lingjing Kong
Kun Zhang
Theofanis Karaletsos
Celestine Mendler-Dünner
Francesco Locatello
KELM
67
0
0
06 Oct 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
236
2
0
01 Oct 2024
Adaptive Recruitment Resource Allocation to Improve Cohort
  Representativeness in Participatory Biomedical Datasets
Adaptive Recruitment Resource Allocation to Improve Cohort Representativeness in Participatory Biomedical Datasets
Muhammad Ahmad
Andrew Estornell
Ellen Wright Clayton
Salvatore Distefano
Russell Rothman
Swalpa Kumar Roy
Danfeng Hong
24
0
0
02 Aug 2024
OxonFair: A Flexible Toolkit for Algorithmic Fairness
OxonFair: A Flexible Toolkit for Algorithmic Fairness
Eoin Delaney
Zihao Fu
Sandra Wachter
Brent Mittelstadt
Chris Russell
FaML
122
3
0
30 Jun 2024
Dataset Representativeness and Downstream Task Fairness
Dataset Representativeness and Downstream Task Fairness
Victor A. Borza
Andrew Estornell
Chien-Ju Ho
Bradley Malin
Yevgeniy Vorobeychik
54
0
0
28 Jun 2024
Differentially Private Worst-group Risk Minimization
Differentially Private Worst-group Risk Minimization
Xinyu Zhou
Raef Bassily
70
3
0
29 Feb 2024
To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair
  Training on Shared Models
To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models
Cyrus Cousins
I. E. Kumar
Suresh Venkatasubramanian
FedML
71
2
0
29 Feb 2024
Fair Classification with Partial Feedback: An Exploration-Based Data
  Collection Approach
Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach
Vijay Keswani
Anay Mehrotra
L. E. Celis
FaML
73
0
0
17 Feb 2024
Falcon: Fair Active Learning using Multi-armed Bandits
Falcon: Fair Active Learning using Multi-armed Bandits
Ki Hyun Tae
Hantian Zhang
Jaeyoung Park
Kexin Rong
Steven Euijong Whang
FaML
60
4
0
23 Jan 2024
Fair Active Learning in Low-Data Regimes
Fair Active Learning in Low-Data Regimes
Romain Camilleri
Andrew Wagenmaker
Jamie Morgenstern
Lalit P. Jain
Kevin Jamieson
FaML
57
1
0
13 Dec 2023
Optimal Multi-Distribution Learning
Optimal Multi-Distribution Learning
Zihan Zhang
Wenhao Zhan
Yuxin Chen
Simon S. Du
Jason D. Lee
83
14
0
08 Dec 2023
Benchmarking Multi-Domain Active Learning on Image Classification
Benchmarking Multi-Domain Active Learning on Image Classification
Jiayi Li
Rohan Taori
Tatsunori Hashimoto
VLM
66
0
0
01 Dec 2023
Agnostic Multi-Group Active Learning
Agnostic Multi-Group Active Learning
Nick Rittler
Kamalika Chaudhuri
44
1
0
02 Jun 2023
Pushing the Accuracy-Group Robustness Frontier with Introspective
  Self-play
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play
J. Liu
Krishnamurthy Dvijotham
Jihyeon Janel Lee
Quan Yuan
Martin Strobel
Balaji Lakshminarayanan
Deepak Ramachandran
70
5
0
11 Feb 2023
Can Strategic Data Collection Improve the Performance of Poverty
  Prediction Models?
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?
satej soman
Emily L. Aiken
Esther Rolf
J. Blumenstock
13
2
0
16 Nov 2022
I Prefer not to Say: Protecting User Consent in Models with Optional
  Personal Data
I Prefer not to Say: Protecting User Consent in Models with Optional Personal Data
Tobias Leemann
Martin Pawelczyk
Christian Thomas Eberle
Gjergji Kasneci
49
1
0
25 Oct 2022
Fair Robust Active Learning by Joint Inconsistency
Fair Robust Active Learning by Joint Inconsistency
Tsung-Han Wu
Hung-Ting Su
Shang-Tse Chen
Winston H. Hsu
AAML
70
1
0
22 Sep 2022
M$^2$DQN: A Robust Method for Accelerating Deep Q-learning Network
M2^22DQN: A Robust Method for Accelerating Deep Q-learning Network
Zhe Zhang
Yukun Zou
Junjie Lai
Qinglong Xu
20
4
0
16 Sep 2022
Representation Bias in Data: A Survey on Identification and Resolution
  Techniques
Representation Bias in Data: A Survey on Identification and Resolution Techniques
N. Shahbazi
Yin Lin
Abolfazl Asudeh
H. V. Jagadish
87
76
0
22 Mar 2022
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep
  Classifiers
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers
Dominik Zietlow
Michael Lohaus
Guha Balakrishnan
Matthäus Kleindessner
Francesco Locatello
Bernhard Schölkopf
Chris Russell
FaML
82
74
0
09 Mar 2022
Adaptive Sampling Strategies to Construct Equitable Training Datasets
Adaptive Sampling Strategies to Construct Equitable Training Datasets
William Cai
R. Encarnación
Bobbie Chern
S. Corbett-Davies
Miranda Bogen
Stevie Bergman
Sharad Goel
161
30
0
31 Jan 2022
Adaptive Data Debiasing through Bounded Exploration
Adaptive Data Debiasing through Bounded Exploration
Yifan Yang
Yang Liu
Parinaz Naghizadeh
FaML
78
7
0
25 Oct 2021
1