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The Empirical Likelihood Approach to Quantifying Uncertainty in Sample
  Average Approximation
v1v2 (latest)

The Empirical Likelihood Approach to Quantifying Uncertainty in Sample Average Approximation

9 April 2016
Henry Lam
Enlu Zhou
ArXiv (abs)PDFHTML

Papers citing "The Empirical Likelihood Approach to Quantifying Uncertainty in Sample Average Approximation"

18 / 18 papers shown
Calibrating Decision Robustness via Inverse Conformal Risk Control
Calibrating Decision Robustness via Inverse Conformal Risk Control
Wenbin Zhou
Shixiang Zhu
118
0
0
09 Oct 2025
Obtaining Explainable Classification Models using Distributionally
  Robust Optimization
Obtaining Explainable Classification Models using Distributionally Robust Optimization
S. Dash
Soumyadip Ghosh
Joao Goncalves
M. Squillante
195
0
0
03 Nov 2023
Smoothed $f$-Divergence Distributionally Robust Optimization
Smoothed fff-Divergence Distributionally Robust Optimization
Zhen-Yan Liu
Bart P. G. Van Parys
Henry Lam
401
9
0
24 Jun 2023
Understanding Deep Generative Models with Generalized Empirical
  Likelihoods
Understanding Deep Generative Models with Generalized Empirical LikelihoodsComputer Vision and Pattern Recognition (CVPR), 2023
Suman V. Ravuri
Mélanie Rey
S. Mohamed
M. Deisenroth
VLM
324
7
0
16 Jun 2023
A Finite Sample Complexity Bound for Distributionally Robust Q-learning
A Finite Sample Complexity Bound for Distributionally Robust Q-learningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Shengbo Wang
Nian Si
Jose H. Blanchet
Zhengyuan Zhou
OODOffRL
485
36
0
26 Feb 2023
A Distributionally Robust Optimization Framework for Extreme Event
  Estimation
A Distributionally Robust Optimization Framework for Extreme Event Estimation
Yuanlu Bai
Henry Lam
Xinyu Zhang
225
5
0
03 Jan 2023
Minimax Optimal Estimation of Stability Under Distribution Shift
Minimax Optimal Estimation of Stability Under Distribution ShiftOperational Research (OR), 2022
Hongseok Namkoong
Yuanzhe Ma
Peter Glynn
394
5
0
13 Dec 2022
Statistical Analysis of Wasserstein Distributionally Robust Estimators
Statistical Analysis of Wasserstein Distributionally Robust Estimators
Jose H. Blanchet
Karthyek Murthy
Viet Anh Nguyen
279
62
0
04 Aug 2021
Reliable Off-policy Evaluation for Reinforcement Learning
Reliable Off-policy Evaluation for Reinforcement Learning
Jie Wang
Rui Gao
H. Zha
OffRL
447
13
0
08 Nov 2020
CoinDICE: Off-Policy Confidence Interval Estimation
CoinDICE: Off-Policy Confidence Interval Estimation
Bo Dai
Ofir Nachum
Yinlam Chow
Lihong Li
Csaba Szepesvári
Dale Schuurmans
OffRL
308
89
0
22 Oct 2020
Distributionally Robust Batch Contextual Bandits
Distributionally Robust Batch Contextual BanditsManagement Sciences (MS), 2020
Nian Si
Fan Zhang
Zhengyuan Zhou
Jose H. Blanchet
OffRL
578
33
0
10 Jun 2020
Distributionally Robust Optimization: A Review
Distributionally Robust Optimization: A ReviewOpen Journal of Mathematical Optimization (OJMO), 2019
Hamed Rahimian
Sanjay Mehrotra
360
224
0
13 Aug 2019
Learning Models with Uniform Performance via Distributionally Robust
  Optimization
Learning Models with Uniform Performance via Distributionally Robust Optimization
John C. Duchi
Hongseok Namkoong
OOD
689
501
0
20 Oct 2018
Data-driven Optimal Cost Selection for Distributionally Robust
  Optimization
Data-driven Optimal Cost Selection for Distributionally Robust Optimization
Jose H. Blanchet
Yang Kang
Fan Zhang
Karthyek Murthy
OOD
340
47
0
19 May 2017
Semi-supervised Learning based on Distributionally Robust Optimization
Semi-supervised Learning based on Distributionally Robust Optimization
Jose H. Blanchet
Yang Kang
OOD
311
32
0
28 Feb 2017
Robust Wasserstein Profile Inference and Applications to Machine
  Learning
Robust Wasserstein Profile Inference and Applications to Machine Learning
Jose H. Blanchet
Yang Kang
Karthyek Murthy
OOD
597
372
0
18 Oct 2016
Statistics of Robust Optimization: A Generalized Empirical Likelihood
  Approach
Statistics of Robust Optimization: A Generalized Empirical Likelihood ApproachMathematics of Operations Research (MOR), 2016
John C. Duchi
Peter Glynn
Hongseok Namkoong
564
363
0
11 Oct 2016
Sample Out-Of-Sample Inference Based on Wasserstein Distance
Sample Out-Of-Sample Inference Based on Wasserstein Distance
Jose H. Blanchet
Yang Kang
344
39
0
04 May 2016
1
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