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1806.08010
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Fairness Without Demographics in Repeated Loss Minimization
20 June 2018
Tatsunori B. Hashimoto
Megha Srivastava
Hongseok Namkoong
Abigail Z. Jacobs
FaML
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Papers citing
"Fairness Without Demographics in Repeated Loss Minimization"
50 / 393 papers shown
Deep Clustering based Fair Outlier Detection
Knowledge Discovery and Data Mining (KDD), 2021
Hanyu Song
Peizhao Li
Hongfu Liu
FaML
169
37
0
09 Jun 2021
Fair Machine Learning under Limited Demographically Labeled Data
Mustafa Safa Ozdayi
Murat Kantarcioglu
Rishabh K. Iyer
FaML
149
3
0
03 Jun 2021
Rawlsian Fair Adaptation of Deep Learning Classifiers
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Kulin Shah
Pooja Gupta
Amit Deshpande
Chiranjib Bhattacharyya
FaML
157
12
0
31 May 2021
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Flavien Prost
Pranjal Awasthi
Nicholas Blumm
A. Kumthekar
Trevor Potter
Li Wei
Xuezhi Wang
Ed H. Chi
Jilin Chen
Alex Beutel
198
16
0
20 May 2021
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features
Web Search and Data Mining (WSDM), 2021
Tianxiang Zhao
Enyan Dai
Kai Shu
Suhang Wang
FaML
289
70
0
29 Apr 2021
Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instability
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Pegah Nokhiz
Aravinda Kanchana Ruwanpathirana
Neal Patwari
Suresh Venkatasubramanian
241
9
0
24 Apr 2021
Individually Fair Gradient Boosting
International Conference on Learning Representations (ICLR), 2021
Alexander Vargo
Fan Zhang
Mikhail Yurochkin
Yuekai Sun
FaML
FedML
195
16
0
31 Mar 2021
Statistical inference for individual fairness
International Conference on Learning Representations (ICLR), 2021
Subha Maity
Songkai Xue
Mikhail Yurochkin
Yuekai Sun
FaML
159
21
0
30 Mar 2021
Federated Learning with Taskonomy for Non-IID Data
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Hadi Jamali Rad
Mohammad Abdizadeh
Anuj Singh
FedML
238
70
0
29 Mar 2021
Tilted Cross Entropy (TCE): Promoting Fairness in Semantic Segmentation
Attila Szabo
Hadi Jamali Rad
Siva-Datta Mannava
131
17
0
25 Mar 2021
Wasserstein Robust Classification with Fairness Constraints
Manufacturing & Service Operations Management (M&SOM), 2021
Yijie Wang
Viet Anh Nguyen
G. A. Hanasusanto
OOD
217
12
0
11 Mar 2021
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data
International Conference on Machine Learning (ICML), 2021
Esther Rolf
Theodora Worledge
Benjamin Recht
Michael I. Jordan
138
45
0
05 Mar 2021
Understanding and Mitigating Accuracy Disparity in Regression
International Conference on Machine Learning (ICML), 2021
Jianfeng Chi
Yuan Tian
Geoffrey J. Gordon
Han Zhao
190
28
0
24 Feb 2021
Technical Challenges for Training Fair Neural Networks
Valeriia Cherepanova
V. Nanda
Micah Goldblum
John P. Dickerson
Tom Goldstein
FaML
131
28
0
12 Feb 2021
Fairness-Aware PAC Learning from Corrupted Data
Journal of machine learning research (JMLR), 2021
Nikola Konstantinov
Christoph H. Lampert
273
22
0
11 Feb 2021
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Nenad Tomašev
Kevin R. McKee
Jackie Kay
Shakir Mohamed
FaML
204
105
0
03 Feb 2021
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
680
535
0
31 Dec 2020
Fair for All: Best-effort Fairness Guarantees for Classification
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
A. Krishnaswamy
Zhihao Jiang
Kangning Wang
Yu Cheng
Kamesh Munagala
FaML
571
11
0
18 Dec 2020
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models
Brittany Johnson
Jesse Bartola
Rico Angell
Katherine Keith
Sam Witty
S. Giguere
Yuriy Brun
FaML
214
21
0
17 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
International Conference on Machine Learning (ICML), 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Abigail Z. Jacobs
OOD
674
1,653
0
14 Dec 2020
Learning how to approve updates to machine learning algorithms in non-stationary settings
Jean Feng
144
1
0
14 Dec 2020
Learning with risks based on M-location
Machine-mediated learning (ML), 2020
Matthew J. Holland
229
10
0
04 Dec 2020
FairBatch: Batch Selection for Model Fairness
International Conference on Learning Representations (ICLR), 2020
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
VLM
401
147
0
03 Dec 2020
How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering
Transactions of the Association for Computational Linguistics (TACL), 2020
Zhengbao Jiang
Jun Araki
Haibo Ding
Graham Neubig
UQCV
425
512
0
02 Dec 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2020
Umang Bhatt
Javier Antorán
Yunfeng Zhang
Q. V. Liao
P. Sattigeri
...
L. Nachman
R. Chunara
Madhulika Srikumar
Adrian Weller
Alice Xiang
326
289
0
15 Nov 2020
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
242
222
0
03 Nov 2020
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness
Conference on Fairness, Accountability and Transparency (FAccT), 2020
Mckane Andrus
Elena Spitzer
Jeffrey Brown
Alice Xiang
339
144
0
30 Oct 2020
Selective Classification Can Magnify Disparities Across Groups
International Conference on Learning Representations (ICLR), 2020
Erik Jones
Shiori Sagawa
Pang Wei Koh
Ananya Kumar
Abigail Z. Jacobs
350
49
0
27 Oct 2020
Nonlinear Monte Carlo Method for Imbalanced Data Learning
Xuli Shen
Qing-Song Xu
Xiangyang Xue
OOD
114
0
0
27 Oct 2020
Coping with Label Shift via Distributionally Robust Optimisation
International Conference on Learning Representations (ICLR), 2020
J.N. Zhang
A. Menon
Andreas Veit
Srinadh Bhojanapalli
Sanjiv Kumar
S. Sra
OOD
317
77
0
23 Oct 2020
How Do Fair Decisions Fare in Long-term Qualification?
Xueru Zhang
Ruibo Tu
Yang Liu
M. Liu
Hedvig Kjellström
Kun Zhang
Cheng Zhang
153
81
0
21 Oct 2020
Environment Inference for Invariant Learning
Elliot Creager
J. Jacobsen
R. Zemel
OOD
765
437
0
14 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization
Daniel Levy
Y. Carmon
John C. Duchi
Aaron Sidford
299
233
0
12 Oct 2020
Fairness-aware Agnostic Federated Learning
SDM (SDM), 2020
Wei Du
Depeng Xu
Xintao Wu
Hanghang Tong
FedML
225
150
0
10 Oct 2020
Utility is in the Eye of the User: A Critique of NLP Leaderboards
Kawin Ethayarajh
Dan Jurafsky
ELM
365
58
0
29 Sep 2020
Worst-Case-Aware Curriculum Learning for Zero and Few Shot Transfer
Sheng Zhang
Xin Zhang
Weiming Zhang
Anders Søgaard
VLM
145
10
0
23 Sep 2020
Beyond Individual and Group Fairness
Pranjal Awasthi
Corinna Cortes
Yishay Mansour
M. Mohri
FaML
239
25
0
21 Aug 2020
BREEDS: Benchmarks for Subpopulation Shift
International Conference on Learning Representations (ICLR), 2020
Shibani Santurkar
Dimitris Tsipras
Aleksander Madry
OOD
218
191
0
11 Aug 2020
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
International Conference on Machine Learning (ICML), 2020
Martin Mladenov
Elliot Creager
Omer Ben-Porat
Kevin Swersky
R. Zemel
Craig Boutilier
311
67
0
31 Jul 2020
Distributionally Robust Losses for Latent Covariate Mixtures
Operational Research (OR), 2020
John C. Duchi
Tatsunori Hashimoto
Hongseok Namkoong
188
87
0
28 Jul 2020
A Distributionally Robust Approach to Fair Classification
Bahar Taşkesen
Viet Anh Nguyen
Daniel Kuhn
Jose H. Blanchet
FaML
233
66
0
18 Jul 2020
Robustness to Spurious Correlations via Human Annotations
International Conference on Machine Learning (ICML), 2020
Megha Srivastava
Tatsunori Hashimoto
Abigail Z. Jacobs
CML
OOD
200
92
0
13 Jul 2020
Tilted Empirical Risk Minimization
Tian Li
Ahmad Beirami
Maziar Sanjabi
Virginia Smith
382
144
0
02 Jul 2020
Debiased Contrastive Learning
Ching-Yao Chuang
Joshua Robinson
Yen-Chen Lin
Antonio Torralba
Stefanie Jegelka
SSL
583
656
0
01 Jul 2020
Fairness without Demographics through Adversarially Reweighted Learning
Neural Information Processing Systems (NeurIPS), 2020
Preethi Lahoti
Alex Beutel
Jilin Chen
Kang Lee
Flavien Prost
Nithum Thain
Xuezhi Wang
Ed H. Chi
FaML
490
371
0
23 Jun 2020
Fair Performance Metric Elicitation
Neural Information Processing Systems (NeurIPS), 2020
Gaurush Hiranandani
Harikrishna Narasimhan
Oluwasanmi Koyejo
232
19
0
23 Jun 2020
Fairness in Forecasting and Learning Linear Dynamical Systems
AAAI Conference on Artificial Intelligence (AAAI), 2020
Quan-Gen Zhou
Jakub Mareˇcek
Robert Shorten
AI4TS
276
7
0
12 Jun 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Abigail Z. Jacobs
569
412
0
09 May 2020
Doubly-stochastic mining for heterogeneous retrieval
A. S. Rawat
A. Menon
Andreas Veit
Felix X. Yu
Sashank J. Reddi
Sanjiv Kumar
127
5
0
23 Apr 2020
Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction
Maxime Cauchois
Suyash Gupta
John C. Duchi
307
14
0
21 Apr 2020
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