Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach

11 October 2016

Papers citing "Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach"

29 / 79 papers shown

Title
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations A. Puli Lily H. Zhang Eric K. Oermann Rajesh Ranganath OOD OODD 27 48 0 29 Jun 2021
Examining and Combating Spurious Features under Distribution Shift Chunting Zhou Xuezhe Ma Paul Michel Graham Neubig OOD 37 67 0 14 Jun 2021
Deeply-Debiased Off-Policy Interval Estimation C. Shi Runzhe Wan Victor Chernozhukov R. Song OffRL 25 36 0 10 May 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
Improving Offline Contextual Bandits with Distributional Robustness Otmane Sakhi Louis Faury Flavian Vasile OffRL 15 7 0 13 Nov 2020
Evaluating Model Robustness and Stability to Dataset Shift Adarsh Subbaswamy R. Adams Suchi Saria OOD 26 9 0 28 Oct 2020
CoinDICE: Off-Policy Confidence Interval Estimation Bo Dai Ofir Nachum Yinlam Chow Lihong Li Csaba Szepesvári Dale Schuurmans OffRL 27 84 0 22 Oct 2020
Minimax Classification with 0-1 Loss and Performance Guarantees Santiago Mazuelas Andrea Zanoni Aritz Pérez Martínez 13 12 0 15 Oct 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 18 79 0 28 Jul 2020
An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectives Qi Qi Zhishuai Guo Yi Tian Xu Rong Jin Tianbao Yang 33 44 0 17 Jun 2020
Risk Variance Penalization Chuanlong Xie Haotian Ye Fei Chen Yue Liu Rui Sun Zhenguo Li 53 33 0 13 Jun 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 33 244 0 11 Feb 2020
Distributionally Robust Deep Learning using Hardness Weighted Sampling Lucas Fidon Michael Aertsen Thomas Deprest Doaa Emam Frédéric Guffens ... Andrew Melbourne Sébastien Ourselin Jan Deprest Georg Langs Tom Kamiel Magda Vercauteren OOD 22 10 0 08 Jan 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 16 1,200 0 20 Nov 2019
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 24 52 0 28 Oct 2019
Distributionally Robust Optimization: A Review Hamed Rahimian Sanjay Mehrotra 19 118 0 13 Aug 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 75 2,165 0 05 Jul 2019
Distributionally Robust Counterfactual Risk Minimization Louis Faury Ugo Tanielian Flavian Vasile E. Smirnova Elvis Dohmatob 25 45 0 14 Jun 2019
Improving Neural Language Modeling via Adversarial Training Dilin Wang Chengyue Gong Qiang Liu AAML 43 115 0 10 Jun 2019
Maximum Weighted Loss Discrepancy Fereshte Khani Aditi Raghunathan Percy Liang 15 16 0 08 Jun 2019
Empirical Likelihood for Contextual Bandits Nikos Karampatziakis John Langford Paul Mineiro OffRL 23 9 0 07 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 32 129 0 24 May 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 20 135 0 24 Jan 2019
Robust Optimization over Multiple Domains Qi Qian Shenghuo Zhu Jiasheng Tang Rong Jin Baigui Sun Hao Li OOD 18 70 0 19 May 2018
Distributionally Robust Submodular Maximization Matthew Staib Bryan Wilder Stefanie Jegelka 31 35 0 14 Feb 2018
Calibration of Distributionally Robust Empirical Optimization Models Jun-ya Gotoh M. J. Kim Andrew E. B. Lim 24 41 0 17 Nov 2017
Robust Wasserstein Profile Inference and Applications to Machine Learning Jose H. Blanchet Yang Kang Karthyek Murthy OOD 19 330 0 18 Oct 2016
Sample Out-Of-Sample Inference Based on Wasserstein Distance Jose H. Blanchet Yang Kang 34 35 0 04 May 2016
Learning without Concentration S. Mendelson 92 333 0 01 Jan 2014