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Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach

11 October 2016

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

50 / 202 papers shown

Title
Scalable Distributional Robustness in a Class of Non Convex Optimization with Guarantees Avinandan Bose Arunesh Sinha Tien Mai 53 5 0 31 May 2022
Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang Linyi Li Maurice Weber Yang Liu Ce Zhang Yue Liu OOD 100 15 0 31 May 2022
PAC Generalization via Invariant Representations Advait Parulekar Karthikeyan Shanmugam Sanjay Shakkottai 93 4 0 30 May 2022
Understanding new tasks through the lens of training data via exponential tilting Subha Maity Mikhail Yurochkin Moulinath Banerjee Yuekai Sun 104 10 0 26 May 2022
Improved Group Robustness via Classifier Retraining on Independent Splits Thien Hai Nguyen Hongyang R. Zhang Huy Le Nguyen OOD 67 2 0 20 Apr 2022
MetaSets: Meta-Learning on Point Sets for Generalizable Representations Chao Huang Zhangjie Cao Yunbo Wang Jianmin Wang Mingsheng Long 3DPC 74 30 0 15 Apr 2022
Rockafellian Relaxation and Stochastic Optimization under Perturbations J. Royset Louis L. Chen Eric Eckstrand 84 5 0 10 Apr 2022
What You See is What You Get: Principled Deep Learning via Distributional Generalization B. Kulynych Yao-Yuan Yang Yaodong Yu Jarosław Błasiok Preetum Nakkiran OOD 78 10 0 07 Apr 2022
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters Tim Tsz-Kit Lau Han Liu OOD 91 2 0 23 Mar 2022
$Distributionally Robust Bayesian Optimization with $\varphi$-divergences$ Distributionally Robust Bayesian Optimization with $\varphi$ -divergences Hisham Husain Vu-Linh Nguyen Anton Van Den Hengel 98 13 0 04 Mar 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 91 13 0 01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 99 45 0 27 Feb 2022
Solving optimization problems with Blackwell approachability Julien Grand-Clément Christian Kroer 48 5 0 24 Feb 2022
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift Alekh Agarwal Tong Zhang OOD 74 29 0 11 Feb 2022
Certifying Out-of-Domain Generalization for Blackbox Functions Maurice Weber Linyi Li Wei Ping Zhikuan Zhao Yue Liu Ce Zhang OOD 64 15 0 03 Feb 2022
Minimax risk classifiers with 0-1 loss Santiago Mazuelas Mauricio Romero Peter Grünwald 101 6 0 17 Jan 2022
Towards Group Robustness in the presence of Partial Group Labels Vishnu Suresh Lokhande Kihyuk Sohn Jinsung Yoon Madeleine Udell Chen-Yu Lee Tomas Pfister OOD 80 11 0 10 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 71 68 0 04 Jan 2022
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity Dixian Zhu Yiming Ying Tianbao Yang 144 11 0 30 Dec 2021
Simple and near-optimal algorithms for hidden stratification and multi-group learning Abdoreza Asadpour Daniel J. Hsu 147 20 0 22 Dec 2021
Balancing Fairness and Robustness via Partial Invariance Moulik Choraria Ibtihal Ferwana Ankur Mani Lav Varshney OOD 66 1 0 17 Dec 2021
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 300 139 0 15 Dec 2021
Higher-Order Coverage Errors of Batching Methods via Edgeworth Expansions on $t$ -Statistics Shengyi He Henry Lam 15 3 0 12 Nov 2021
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features Haohan Wang Zeyi Huang Hanlin Zhang Yong Jae Lee Eric P. Xing OOD 200 16 0 05 Nov 2021
Coordinate Linear Variance Reduction for Generalized Linear Programming Chaobing Song Cheuk Yin Lin Stephen J. Wright Jelena Diakonikolas 89 13 0 02 Nov 2021
Identifying and Benchmarking Natural Out-of-Context Prediction Problems David Madras D. Psaltis CML OOD 105 4 0 25 Oct 2021
Learning Representations that Support Robust Transfer of Predictors Yilun Xu Tommi Jaakkola OOD 42 26 0 19 Oct 2021
A Survey of Learning Criteria Going Beyond the Usual Risk Matthew J. Holland Kazuki Tanabe FaML 63 4 0 11 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 143 40 0 24 Sep 2021
Distributionally Robust Multilingual Machine Translation Chunting Zhou Daniel Levy Xian Li Marjan Ghazvininejad Graham Neubig 139 24 0 09 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 168 536 0 31 Aug 2021
Unsupervised Learning of Debiased Representations with Pseudo-Attributes Seonguk Seo Joon-Young Lee Bohyung Han FaML 124 50 0 06 Aug 2021
Statistical Analysis of Wasserstein Distributionally Robust Estimators Jose H. Blanchet Karthyek Murthy Viet Anh Nguyen 67 48 0 04 Aug 2021
Just Train Twice: Improving Group Robustness without Training Group Information Emmy Liu Behzad Haghgoo Annie S. Chen Aditi Raghunathan Pang Wei Koh Shiori Sagawa Percy Liang Chelsea Finn OOD 118 563 0 19 Jul 2021
Mandoline: Model Evaluation under Distribution Shift Mayee F. Chen Karan Goel N. Sohoni Fait Poms Kayvon Fatahalian Christopher Ré 87 72 0 01 Jul 2021
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations A. Puli Lily H. Zhang Eric K. Oermann Rajesh Ranganath OOD OODD 85 49 0 29 Jun 2021
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization Yibo Zeng Henry Lam 119 8 0 21 Jun 2021
Distributionally Robust Martingale Optimal Transport Zhengqing Zhou Jose H. Blanchet Peter Glynn OT 21 1 0 14 Jun 2021
Examining and Combating Spurious Features under Distribution Shift Chunting Zhou Xuezhe Ma Paul Michel Graham Neubig OOD 89 68 0 14 Jun 2021
Distributionally Robust Optimization with Markovian Data Mengmeng Li Tobias Sutter Daniel Kuhn 39 9 0 12 Jun 2021
Measuring Generalization with Optimal Transport Ching-Yao Chuang Youssef Mroueh Kristjan Greenewald Antonio Torralba Stefanie Jegelka OT 90 27 0 07 Jun 2021
Efficient Online-Bandit Strategies for Minimax Learning Problems Christophe Roux Elias Wirth Sebastian Pokutta Thomas Kerdreux 49 2 0 28 May 2021
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving Julien Grand-Clément Christian Kroer 47 5 0 27 May 2021
Deeply-Debiased Off-Policy Interval Estimation C. Shi Runzhe Wan Victor Chernozhukov R. Song OffRL 53 38 0 10 May 2021
Towards Theoretical Understandings of Robust Markov Decision Processes: Sample Complexity and Asymptotics Wenhao Yang Liangyu Zhang Zhihua Zhang 72 35 0 09 May 2021
On the Optimality of Batch Policy Optimization Algorithms Chenjun Xiao Yifan Wu Tor Lattimore Bo Dai Jincheng Mei Lihong Li Csaba Szepesvári Dale Schuurmans OffRL 72 33 0 06 Apr 2021
Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles Robik Shrestha Jinkyu Lee Kushal Kafle S. Hwang Il Yong Chun 79 1 0 01 Apr 2021
Statistical inference for individual fairness Subha Maity Songkai Xue Mikhail Yurochkin Yuekai Sun FaML 64 20 0 30 Mar 2021
Modeling the Second Player in Distributionally Robust Optimization Paul Michel Tatsunori Hashimoto Graham Neubig 66 33 0 18 Mar 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 64 7 0 16 Feb 2021