Learning Bounds for Risk-sensitive Learning

15 June 2020

Sejun Park

Papers citing "Learning Bounds for Risk-sensitive Learning"

33 / 33 papers shown

Title
Robust Federated Learning with Global Sensitivity Estimation for Financial Risk Management Lei Zhao Lin Cai Wu-Sheng Lu FedML 81 0 0 24 Feb 2025
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 Matthew J. Holland Toma Hamada OOD 28 0 0 07 Aug 2024
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 Ayon Ghosh Prashanth L.A. Krishna Jagannathan 23 0 0 31 May 2024
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 Matthew J. Holland 26 2 0 15 Feb 2024
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 Thomas Pethick Grigorios G. Chrysos V. Cevher 16 6 0 17 Feb 2023
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 Matthew J. Holland 28 1 0 27 Jan 2023
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 Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 32 6 0 10 Dec 2022
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 Shu Hu Xin Wang Siwei Lyu 30 32 0 18 Jul 2022
Supervised Learning with General Risk Functionals Liu Leqi Audrey Huang Zachary Chase Lipton Kamyar Azizzadenesheli 11 5 0 27 Jun 2022
Flexible risk design using bi-directional dispersion Matthew J. Holland 32 5 0 28 Mar 2022
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 Vishwajit Hegde Arvind S. Menon L. A. Prashanth Krishna Jagannathan 19 2 0 16 Nov 2021
Neural Network Pruning Through Constrained Reinforcement Learning Shehryar Malik Muhammad Umair Haider O. Iqbal M. Taj 24 0 0 16 Oct 2021
A Survey of Learning Criteria Going Beyond the Usual Risk Matthew J. Holland Kazuki Tanabe FaML 24 4 0 11 Oct 2021
Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids Shanny Lin Shaohui Liu Hao Zhu 15 9 0 04 Oct 2021
A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits Joel Q. L. Chang Vincent Y. F. Tan 24 13 0 25 Aug 2021
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 Ming Liang Ang Eloise Y. Y. Lim Joel Q. L. Chang 8 1 0 14 May 2021
Spectral risk-based learning using unbounded losses Matthew J. Holland El Mehdi Haress 16 10 0 11 May 2021
Off-Policy Risk Assessment in Contextual Bandits Audrey Huang Liu Leqi Zachary Chase Lipton Kamyar Azizzadenesheli OffRL 27 36 0 18 Apr 2021
Noisy Linear Convergence of Stochastic Gradient Descent for CV@R Statistical Learning under Polyak-Łojasiewicz Conditions Dionysios S. Kalogerias 22 8 0 14 Dec 2020
Robust Unsupervised Learning via L-Statistic Minimization Andreas Maurer D. A. Parletta Andrea Paudice Massimiliano Pontil OOD 19 0 0 14 Dec 2020
Learning with risks based on M-location Matthew J. Holland 11 9 0 04 Dec 2020
Risk-Constrained Thompson Sampling for CVaR Bandits Joel Q. L. Chang Qiuyu Zhu Vincent Y. F. Tan 11 13 0 16 Nov 2020
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 24 51 0 28 Oct 2019
A Wasserstein distance approach for concentration of empirical risk estimates A. PrashanthL. S. Bhat 23 20 0 27 Feb 2019