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1905.10943
Cited By
Distributionally Robust Optimization and Generalization in Kernel Methods
27 May 2019
Matthew Staib
Stefanie Jegelka
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Papers citing
"Distributionally Robust Optimization and Generalization in Kernel Methods"
34 / 34 papers shown
Title
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Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference
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Rejection via Learning Density Ratios
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Uncertainty Quantification on Graph Learning: A Survey
Chao Chen
Chenghua Guo
Rui Xu
Xiangwen Liao
Xi Zhang
Sihong Xie
Hui Xiong
Mohit Bansal
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23 Apr 2024
Towards Generalizing Inferences from Trials to Target Populations
Melody Y Huang
Harsh Parikh
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FedDRO: Federated Compositional Optimization for Distributionally Robust Learning
Prashant Khanduri
Chengyin Li
Rafi Ibn Sultan
Yao Qiang
Joerg Kliewer
Dongxiao Zhu
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21 Nov 2023
Smoothed
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Zhen-Yan Liu
Bart P. G. Van Parys
Henry Lam
58
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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
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0
12 Jun 2023
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
Lijun Zhang
Haomin Bai
W. Tu
Ping Yang
Yao Hu
113
4
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31 May 2023
Online Kernel CUSUM for Change-Point Detection
S. Wei
Yao Xie
99
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28 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou
Parnian Kassraie
Anastasis Kratsios
Andreas Krause
Jonas Rothfuss
108
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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
109
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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
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0
18 Aug 2022
Distributionally Robust Bayesian Optimization with
φ
\varphi
φ
-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
82
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11 Feb 2022
Holistic Deep Learning
Dimitris Bertsimas
Kimberly Villalobos Carballo
L. Boussioux
M. Li
Alex Paskov
I. Paskov
66
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
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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
76
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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
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0
20 Feb 2020
Distributionally Robust Bayesian Quadrature Optimization
Thanh Tang Nguyen
Sunil R. Gupta
Huong Ha
Santu Rana
Svetha Venkatesh
47
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
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