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Learning Bounds for Risk-sensitive Learning

Learning Bounds for Risk-sensitive Learning

15 June 2020
Jaeho Lee
Sejun Park
Jinwoo Shin
ArXivPDFHTML

Papers citing "Learning Bounds for Risk-sensitive Learning"

33 / 33 papers shown
Title
Robust Federated Learning with Global Sensitivity Estimation for Financial Risk Management
Robust Federated Learning with Global Sensitivity Estimation for Financial Risk Management
Lei Zhao
Lin Cai
Wu-Sheng Lu
FedML
78
0
0
24 Feb 2025
Generalization Error of the Tilted Empirical Risk
Generalization Error of the Tilted Empirical Risk
Gholamali Aminian
Amir R. Asadi
Tian Li
Ahmad Beirami
G. Reinert
Samuel N. Cohen
21
1
0
28 Sep 2024
Making Robust Generalizers Less Rigid with Soft Ascent-Descent
Making Robust Generalizers Less Rigid with Soft Ascent-Descent
Matthew J. Holland
Toma Hamada
OOD
28
0
0
07 Aug 2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang
Boxiang Lyu
Shuang Qiu
Mladen Kolar
Tong Zhang
OffRL
30
0
0
10 Jul 2024
Concentration Bounds for Optimized Certainty Equivalent Risk Estimation
Concentration Bounds for Optimized Certainty Equivalent Risk Estimation
Ayon Ghosh
Prashanth L.A.
Krishna Jagannathan
23
0
0
31 May 2024
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
Rui Liu
Erfaun Noorani
Pratap Tokekar
John S. Baras
23
1
0
13 Mar 2024
Criterion Collapse and Loss Distribution Control
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
26
2
0
15 Feb 2024
Understanding Contrastive Learning via Distributionally Robust
  Optimization
Understanding Contrastive Learning via Distributionally Robust Optimization
Junkang Wu
Jiawei Chen
Jiancan Wu
Wentao Shi
Xiang Wang
Xiangnan He
24
24
0
17 Oct 2023
Revisiting adversarial training for the worst-performing class
Revisiting adversarial training for the worst-performing class
Thomas Pethick
Grigorios G. Chrysos
V. Cevher
10
6
0
17 Feb 2023
Regret Bounds for Markov Decision Processes with Recursive Optimized
  Certainty Equivalents
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
Wenkun Xu
Xuefeng Gao
X. He
20
10
0
30 Jan 2023
Robust variance-regularized risk minimization with concomitant scaling
Robust variance-regularized risk minimization with concomitant scaling
Matthew J. Holland
26
1
0
27 Jan 2023
Quantile Risk Control: A Flexible Framework for Bounding the Probability
  of High-Loss Predictions
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions
Jake C. Snell
Thomas P. Zollo
Zhun Deng
T. Pitassi
R. Zemel
24
8
0
27 Dec 2022
Stochastic Optimization for Spectral Risk Measures
Stochastic Optimization for Spectral Risk Measures
Ronak R. Mehta
Vincent Roulet
Krishna Pillutla
Lang Liu
Zaïd Harchaoui
27
6
0
10 Dec 2022
Probable Domain Generalization via Quantile Risk Minimization
Probable Domain Generalization via Quantile Risk Minimization
Cian Eastwood
Alexander Robey
Shashank Singh
Julius von Kügelgen
Hamed Hassani
George J. Pappas
Bernhard Schölkopf
OOD
27
61
0
20 Jul 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
26
32
0
18 Jul 2022
Supervised Learning with General Risk Functionals
Supervised Learning with General Risk Functionals
Liu Leqi
Audrey Huang
Zachary Chase Lipton
Kamyar Azizzadenesheli
9
5
0
27 Jun 2022
Flexible risk design using bi-directional dispersion
Flexible risk design using bi-directional dispersion
Matthew J. Holland
20
5
0
28 Mar 2022
Almost Optimal Variance-Constrained Best Arm Identification
Almost Optimal Variance-Constrained Best Arm Identification
Yunlong Hou
Vincent Y. F. Tan
Zixin Zhong
16
10
0
25 Jan 2022
Online Estimation and Optimization of Utility-Based Shortfall Risk
Online Estimation and Optimization of Utility-Based Shortfall Risk
Vishwajit Hegde
Arvind S. Menon
L. A. Prashanth
Krishna Jagannathan
19
2
0
16 Nov 2021
Neural Network Pruning Through Constrained Reinforcement Learning
Neural Network Pruning Through Constrained Reinforcement Learning
Shehryar Malik
Muhammad Umair Haider
O. Iqbal
M. Taj
21
0
0
16 Oct 2021
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
22
4
0
11 Oct 2021
Risk-Aware Learning for Scalable Voltage Optimization in Distribution
  Grids
Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids
Shanny Lin
Shaohui Liu
Hao Zhu
10
9
0
04 Oct 2021
A Unifying Theory of Thompson Sampling for Continuous Risk-Averse
  Bandits
A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits
Joel Q. L. Chang
Vincent Y. F. Tan
16
13
0
25 Aug 2021
DORO: Distributional and Outlier Robust Optimization
DORO: Distributional and Outlier Robust Optimization
Runtian Zhai
Chen Dan
J. Zico Kolter
Pradeep Ravikumar
12
58
0
11 Jun 2021
Thompson Sampling for Gaussian Entropic Risk Bandits
Thompson Sampling for Gaussian Entropic Risk Bandits
Ming Liang Ang
Eloise Y. Y. Lim
Joel Q. L. Chang
8
1
0
14 May 2021
Spectral risk-based learning using unbounded losses
Spectral risk-based learning using unbounded losses
Matthew J. Holland
El Mehdi Haress
13
10
0
11 May 2021
Off-Policy Risk Assessment in Contextual Bandits
Off-Policy Risk Assessment in Contextual Bandits
Audrey Huang
Liu Leqi
Zachary Chase Lipton
Kamyar Azizzadenesheli
OffRL
25
36
0
18 Apr 2021
Noisy Linear Convergence of Stochastic Gradient Descent for CV@R
  Statistical Learning under Polyak-Łojasiewicz Conditions
Noisy Linear Convergence of Stochastic Gradient Descent for CV@R Statistical Learning under Polyak-Łojasiewicz Conditions
Dionysios S. Kalogerias
20
8
0
14 Dec 2020
Robust Unsupervised Learning via L-Statistic Minimization
Robust Unsupervised Learning via L-Statistic Minimization
Andreas Maurer
D. A. Parletta
Andrea Paudice
Massimiliano Pontil
OOD
8
0
0
14 Dec 2020
Learning with risks based on M-location
Learning with risks based on M-location
Matthew J. Holland
9
9
0
04 Dec 2020
Risk-Constrained Thompson Sampling for CVaR Bandits
Risk-Constrained Thompson Sampling for CVaR Bandits
Joel Q. L. Chang
Qiuyu Zhu
Vincent Y. F. Tan
6
13
0
16 Nov 2020
Adaptive Sampling for Stochastic Risk-Averse Learning
Adaptive Sampling for Stochastic Risk-Averse Learning
Sebastian Curi
Kfir Y. Levy
Stefanie Jegelka
Andreas Krause
13
51
0
28 Oct 2019
A Wasserstein distance approach for concentration of empirical risk
  estimates
A Wasserstein distance approach for concentration of empirical risk estimates
A. PrashanthL.
S. Bhat
21
20
0
27 Feb 2019
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