Distributionally Robust Optimization and Generalization in Kernel Methods

27 May 2019

Papers citing "Distributionally Robust Optimization and Generalization in Kernel Methods"

34 / 34 papers shown

Title
Evaluating Model Performance Under Worst-case Subpopulations Mike Li Hongseok Namkoong Shangzhou Xia 96 18 0 01 Jul 2024
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference Vyacheslav Kungurtsev Apaar Aarya Khandelwal Parth Sandeep Rastogi Bapi Chatterjee Jakub Mareˇcek BDL 46 0 0 25 Jun 2024
Rejection via Learning Density Ratios Alexander Soen Hisham Husain Philip Schulz Vu-Linh Nguyen 135 2 0 29 May 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Mohit Bansal AI4CE 86 1 0 23 Apr 2024
Towards Generalizing Inferences from Trials to Target Populations Melody Y Huang Harsh Parikh 55 2 0 26 Feb 2024
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning Prashant Khanduri Chengyin Li Rafi Ibn Sultan Yao Qiang Joerg Kliewer Dongxiao Zhu 87 0 0 21 Nov 2023
Smoothed $f$ -Divergence Distributionally Robust Optimization Zhen-Yan Liu Bart P. G. Van Parys Henry Lam 58 6 0 24 Jun 2023
Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning Haozhe Jasper Wang Chao Du Panyan Fang Li He Liangji Wang Bo Zheng 80 7 0 12 Jun 2023
Efficient Stochastic Approximation of Minimax Excess Risk Optimization Lijun Zhang Haomin Bai W. Tu Ping Yang Yao Hu 113 4 0 31 May 2023
Online Kernel CUSUM for Change-Point Detection S. Wei Yao Xie 99 12 0 28 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 108 6 0 02 Nov 2022
Stochastic Constrained DRO with a Complexity Independent of Sample Size Q. Qi Jiameng Lyu Kung-Sik Chan E. Bai Tianbao Yang 111 16 0 11 Oct 2022
Domain-Specific Risk Minimization for Out-of-Distribution Generalization Yi-Fan Zhang Jindong Wang Jian Liang Zhang Zhang Baosheng Yu Liangdao Wang Dacheng Tao Xingxu Xie OOD 119 17 0 18 Aug 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
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift Alekh Agarwal Tong Zhang OOD 85 29 0 11 Feb 2022
Holistic Deep Learning Dimitris Bertsimas Kimberly Villalobos Carballo L. Boussioux M. Li Alex Paskov I. Paskov 81 2 0 29 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 143 40 0 24 Sep 2021
A Note on Optimizing Distributions using Kernel Mean Embeddings Boris Muzellec Francis R. Bach Alessandro Rudi 37 4 0 18 Jun 2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik Léon Bottou FaML 77 19 0 17 Jun 2021
Distributionally Robust Optimization with Markovian Data Mengmeng Li Tobias Sutter Daniel Kuhn 39 9 0 12 Jun 2021
Robust Generalization despite Distribution Shift via Minimum Discriminating Information Tobias Sutter Andreas Krause Daniel Kuhn OOD 54 10 0 08 Jun 2021
Robust Graph Learning Under Wasserstein Uncertainty Xiang Zhang Yinfei Xu Qinghe Liu Zhicheng Liu Jian Lu Qiao Wang OOD 80 4 0 10 May 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 64 7 0 16 Feb 2021
Two-sample Test using Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 107 21 0 22 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization Daniel Levy Y. Carmon John C. Duchi Aaron Sidford 89 217 0 12 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 184 313 0 24 Sep 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 77 81 0 28 Jul 2020
Robust Bayesian Classification Using an Optimistic Score Ratio Viet Anh Nguyen Nian Si Jose H. Blanchet 81 13 0 08 Jul 2020
Kernel Distributionally Robust Optimization Jia Jie Zhu Wittawat Jitkrittum Moritz Diehl Bernhard Schölkopf 105 16 0 12 Jun 2020
Principled learning method for Wasserstein distributionally robust optimization with local perturbations Yongchan Kwon Wonyoung Hedge Kim Joong-Ho Won M. Paik 96 12 0 05 Jun 2020
Distributionally Robust Bayesian Optimization Johannes Kirschner Ilija Bogunovic Stefanie Jegelka Andreas Krause 113 79 0 20 Feb 2020
Distributionally Robust Bayesian Quadrature Optimization Thanh Tang Nguyen Sunil R. Gupta Huong Ha Santu Rana Svetha Venkatesh 55 28 0 19 Jan 2020
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 153 54 0 28 Oct 2019
Distributionally Robust Optimization: A Review Hamed Rahimian Sanjay Mehrotra 74 134 0 13 Aug 2019