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Tilted Empirical Risk Minimization
v1v2 (latest)

Tilted Empirical Risk Minimization

2 July 2020
Tian Li
Ahmad Beirami
Maziar Sanjabi
Virginia Smith
ArXiv (abs)PDFHTML

Papers citing "Tilted Empirical Risk Minimization"

50 / 88 papers shown
Risk-Entropic Flow Matching
Risk-Entropic Flow Matching
Vahid R. Ramezani
Benjamin Englard
78
0
0
28 Nov 2025
Enhancing Diffusion Model Guidance through Calibration and Regularization
Enhancing Diffusion Model Guidance through Calibration and Regularization
Seyed Alireza Javid
Amirhossein Bagheri
Nuria González-Prelcic
244
0
0
08 Nov 2025
Stress-Aware Learning under KL Drift via Trust-Decayed Mirror Descent
Stress-Aware Learning under KL Drift via Trust-Decayed Mirror Descent
Gabriel Nixon Raj
139
0
0
17 Oct 2025
Robust Fine-Tuning from Non-Robust Pretrained Models: Mitigating Suboptimal Transfer With Epsilon-Scheduling
Robust Fine-Tuning from Non-Robust Pretrained Models: Mitigating Suboptimal Transfer With Epsilon-Scheduling
Jonas Ngnawé
M. Heuillet
Sabyasachi Sahoo
Y. Pequignot
Ola Ahmad
Audrey Durand
Frédéric Precioso
Christian Gagné
AAML
221
0
0
27 Sep 2025
Benefits of Online Tilted Empirical Risk Minimization: A Case Study of Outlier Detection and Robust Regression
Benefits of Online Tilted Empirical Risk Minimization: A Case Study of Outlier Detection and Robust Regression
Yigit E. Yildirim
Samet Demir
Zafer Dogan
137
0
0
18 Sep 2025
Balanced Sharpness-Aware Minimization for Imbalanced Regression
Balanced Sharpness-Aware Minimization for Imbalanced Regression
Yahao Liu
Qin Wang
Lixin Duan
Wen Li
254
2
0
23 Aug 2025
Achieving Distributive Justice in Federated Learning via Uncertainty Quantification
Achieving Distributive Justice in Federated Learning via Uncertainty Quantification
Alycia N. Carey
Xintao Wu
FedML
359
0
0
22 Apr 2025
FedTilt: Towards Multi-Level Fairness-Preserving and Robust Federated Learning
FedTilt: Towards Multi-Level Fairness-Preserving and Robust Federated Learning
Binghui Zhang
Luis Mares De La Cruz
Binghui Wang
FedML
203
1
0
15 Mar 2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang
Yu Zhang
Peng Zhao
Zhi Zhou
416
4
0
01 Mar 2025
Over-the-Air Fair Federated Learning via Multi-Objective Optimization
Over-the-Air Fair Federated Learning via Multi-Objective OptimizationIEEE Communications Letters (IEEE Commun. Lett.), 2025
Shayan Mohajer Hamidi
Ali Bereyhi
S. Asaad
H. Vincent Poor
300
5
0
08 Jan 2025
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting
  Rare Concepts in Foundation Models
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation ModelsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Aashiq Muhamed
Mona Diab
Virginia Smith
279
12
0
01 Nov 2024
Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
Meitong Liu
Xiaoyuan Zhang
Chulin Xie
Kate Donahue
Han Zhao
479
5
0
29 Oct 2024
FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits
  Allocation
FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits AllocationInternational Conference on Speech Technology and Human-Computer Dialogue (ICSTHD), 2024
Zhichao Wang
Lin Wang
Yongxin Guo
Ying-Jun Angela Zhang
Xiaoying Tang
FedML
197
1
0
26 Oct 2024
A New Perspective to Boost Performance Fairness for Medical Federated
  Learning
A New Perspective to Boost Performance Fairness for Medical Federated LearningInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024
Yunlu Yan
Lei Zhu
Yuexiang Li
Xinxing Xu
Rick Siow Mong Goh
Yong Liu
Salman Khan
Chun-Mei Feng
FedMLOOD
309
2
0
12 Oct 2024
Generalization and Robustness of the Tilted Empirical Risk
Generalization and Robustness of the Tilted Empirical Risk
Gholamali Aminian
Amir R. Asadi
Tian Li
Ahmad Beirami
Gesine Reinert
Samuel N. Cohen
518
1
0
28 Sep 2024
Trimming the Risk: Towards Reliable Continuous Training for Deep
  Learning Inspection Systems
Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems
Altaf Allah Abbassi
Houssem Ben Braiek
Foutse Khomh
Thomas Reid
228
1
0
13 Sep 2024
Iterative thresholding for non-linear learning in the strong
  $\varepsilon$-contamination model
Iterative thresholding for non-linear learning in the strong ε\varepsilonε-contamination model
Arvind Rathnashyam
Alex Gittens
162
0
0
05 Sep 2024
On the KL-Divergence-based Robust Satisficing Model
On the KL-Divergence-based Robust Satisficing Model
Haojie Yan
Minglong Zhou
Jiayi Guo
280
2
0
17 Aug 2024
Semi-Variance Reduction for Fair Federated Learning
Semi-Variance Reduction for Fair Federated Learning
Saber Malekmohammadi
Yaoliang Yu
FedML
467
2
0
23 Jun 2024
Bridging Multicalibration and Out-of-distribution Generalization Beyond
  Covariate Shift
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
Jiayun Wu
Tianyu Wang
Peng Cui
Zhiwei Steven Wu
281
12
0
02 Jun 2024
Pursuing Overall Welfare in Federated Learning through Sequential
  Decision Making
Pursuing Overall Welfare in Federated Learning through Sequential Decision Making
S. Hahn
Gi-Soo Kim
Junghye Lee
FedML
315
2
0
31 May 2024
Differentially Private Clustered Federated Learning
Differentially Private Clustered Federated Learning
Saber Malekmohammadi
Afaf Taik
G. Farnadi
FedML
408
2
0
29 May 2024
The Future of Large Language Model Pre-training is Federated
The Future of Large Language Model Pre-training is Federated
Lorenzo Sani
Alexandru Iacob
Zeyu Cao
Bill Marino
Yan Gao
...
Wanru Zhao
William F. Shen
Preslav Aleksandrov
Xinchi Qiu
Nicholas D. Lane
AI4CE
503
43
0
17 May 2024
Two Heads are Better than One: Nested PoE for Robust Defense Against
  Multi-Backdoors
Two Heads are Better than One: Nested PoE for Robust Defense Against Multi-BackdoorsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Victoria Graf
Qin Liu
Muhao Chen
AAML
287
13
0
02 Apr 2024
Criterion Collapse and Loss Distribution Control
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
331
2
0
15 Feb 2024
AdaFed: Fair Federated Learning via Adaptive Common Descent Direction
AdaFed: Fair Federated Learning via Adaptive Common Descent Direction
Shayan Mohajer Hamidi
En-Hui Yang
FedML
298
15
0
10 Jan 2024
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
f-FERM: A Scalable Framework for Robust Fair Empirical Risk MinimizationInternational Conference on Learning Representations (ICLR), 2023
Sina Baharlouei
Shivam Patel
Meisam Razaviyayn
483
4
0
06 Dec 2023
Improving Robustness via Tilted Exponential Layer: A
  Communication-Theoretic Perspective
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic PerspectiveInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Bhagyashree Puranik
Ahmad Beirami
Yao Qin
Upamanyu Madhow
AAML
475
1
0
02 Nov 2023
A minimax optimal control approach for robust neural ODEs
A minimax optimal control approach for robust neural ODEsEuropean Control Conference (ECC), 2023
Cristina Cipriani
Alessandro Scagliotti
Tobias Wöhrer
AAML
366
6
0
26 Oct 2023
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced
  Variance
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced Variance
Dun Zeng
Zenglin Xu
Yu Pan
Xu Luo
Qifan Wang
Xiaoying Tang
FedML
347
1
0
04 Oct 2023
Error Norm Truncation: Robust Training in the Presence of Data Noise for
  Text Generation Models
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation ModelsInternational Conference on Learning Representations (ICLR), 2023
Tianjian Li
Haoran Xu
Philipp Koehn
Daniel Khashabi
Kenton W. Murray
250
6
0
02 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda
  for Developing Practical Guidelines and Tools
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and ToolsConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023
Maximilian Schambach
Rakshit Naidu
Rayid Ghani
Kit T. Rodolfa
Daniel E. Ho
Hoda Heidari
FaML
323
24
0
29 Sep 2023
Mitigating Group Bias in Federated Learning for Heterogeneous Devices
Mitigating Group Bias in Federated Learning for Heterogeneous DevicesConference on Fairness, Accountability and Transparency (FAccT), 2023
Khotso Selialia
Yasra Chandio
Fatima M. Anwar
FedML
364
8
0
13 Sep 2023
Addressing Distribution Shift in RTB Markets via Exponential Tilting
Addressing Distribution Shift in RTB Markets via Exponential Tilting
Minji Kim
Seong Jin Lee
B. Kim
61
1
0
14 Aug 2023
Scaff-PD: Communication Efficient Fair and Robust Federated Learning
Scaff-PD: Communication Efficient Fair and Robust Federated Learning
Yaodong Yu
Sai Praneeth Karimireddy
Yi-An Ma
Michael I. Jordan
FedML
410
5
0
25 Jul 2023
Stochastic Re-weighted Gradient Descent via Distributionally Robust
  Optimization
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
Ramnath Kumar
Kushal Majmundar
Dheeraj M. Nagaraj
A. Suggala
ODL
486
8
0
15 Jun 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey
Fairness and Privacy-Preserving in Federated Learning: A SurveyInformation Fusion (Inf. Fusion), 2023
Taki Hasan Rafi
Faiza Anan Noor
Tahmid Hussain
Dong-Kyu Chae
FedML
401
94
0
14 Jun 2023
Fair yet Asymptotically Equal Collaborative Learning
Fair yet Asymptotically Equal Collaborative LearningInternational Conference on Machine Learning (ICML), 2023
Xiaoqiang Lin
Xinyi Xu
See-Kiong Ng
Chuan-Sheng Foo
Bryan Kian Hsiang Low
FedML
229
14
0
09 Jun 2023
Federated Learning under Covariate Shifts with Generalization Guarantees
Federated Learning under Covariate Shifts with Generalization Guarantees
Ali Ramezani-Kebrya
Fanghui Liu
Thomas Pethick
Grigorios G. Chrysos
Volkan Cevher
FedMLOOD
391
12
0
08 Jun 2023
Can Fair Federated Learning reduce the need for Personalisation?
Can Fair Federated Learning reduce the need for Personalisation?
Ferhat Ozgur Catak
Pedro Gusmão
S. Sarp
FedML
185
1
0
04 May 2023
Revisiting adversarial training for the worst-performing class
Revisiting adversarial training for the worst-performing class
Thomas Pethick
Grigorios G. Chrysos
Volkan Cevher
206
7
0
17 Feb 2023
From Utilitarian to Rawlsian Designs for Algorithmic Fairness
From Utilitarian to Rawlsian Designs for Algorithmic Fairness
Daniel E. Rigobon
FaML
278
2
0
07 Feb 2023
Meta-Learning Mini-Batch Risk Functionals
Meta-Learning Mini-Batch Risk Functionals
Jacob Tyo
Zachary Chase Lipton
277
0
0
27 Jan 2023
Robust variance-regularized risk minimization with concomitant scaling
Robust variance-regularized risk minimization with concomitant scalingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Matthew J. Holland
432
1
0
27 Jan 2023
Corruption-tolerant Algorithms for Generalized Linear Models
Corruption-tolerant Algorithms for Generalized Linear ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022
B. Mukhoty
Debojyoti Dey
Purushottam Kar
170
1
0
11 Dec 2022
Stochastic Optimization for Spectral Risk Measures
Stochastic Optimization for Spectral Risk MeasuresInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Ronak R. Mehta
Vincent Roulet
Krishna Pillutla
Lang Liu
Zaïd Harchaoui
220
9
0
10 Dec 2022
On Proper Learnability between Average- and Worst-case Robustness
On Proper Learnability between Average- and Worst-case RobustnessNeural Information Processing Systems (NeurIPS), 2022
Vinod Raman
Unique Subedi
Ambuj Tewari
457
4
0
10 Nov 2022
Outlier-Robust Group Inference via Gradient Space Clustering
Outlier-Robust Group Inference via Gradient Space Clustering
Yuchen Zeng
Kristjan Greenewald
Kangwook Lee
Justin Solomon
Mikhail Yurochkin
193
2
0
13 Oct 2022
Fairness via Adversarial Attribute Neighbourhood Robust Learning
Fairness via Adversarial Attribute Neighbourhood Robust Learning
Q. Qi
Shervin Ardeshir
Yi Tian Xu
Tianbao Yang
302
0
0
12 Oct 2022
Stochastic Constrained DRO with a Complexity Independent of Sample Size
Stochastic Constrained DRO with a Complexity Independent of Sample Size
Q. Qi
Jiameng Lyu
Kung-Sik Chan
E. Bai
Tianbao Yang
323
19
0
11 Oct 2022
12
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