Hongseok Namkoong

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John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Ludwig SchmidtStanford University and AnthropicVerified email at cs.washington.edu
Steve YadlowskyResearch Scientist, Google DeepMindVerified email at google.com
Tatsunori HashimotoAssistant Professor, StanfordVerified email at stanford.edu
Peter W. GlynnProfessor of Management Science and EngineeringVerified email at stanford.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Jong Wook KimOpenAIVerified email at openai.com
Ethan W. CheColumbia UniversityVerified email at columbia.edu
Tiffany CaiStatistics PhD student, Columbia UniversityVerified email at columbia.edu
Emma BrunskillAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Jiashuo LiuPh.D. Candidate @Tsinghua | Visiting Ph.D. @Stanford, CambridgeVerified email at mails.tsinghua.edu.cn
Andrew SiahColumbia UniversityVerified email at columbia.edu
Naimeng YePh.D. Student, Columbia UniversityVerified email at columbia.edu
Tianyu WangColumbia UniversityVerified email at columbia.edu
Yuanzhe MaColumbia UniversityVerified email at columbia.edu
Ari BoyarskyColumbia UniversityVerified email at columbia.edu
Jean Pouget-AbadieGoogle ResearchVerified email at google.com
Eytan BakshyResearch Director, MetaVerified email at fb.com
Jing DongColumbia UniversityVerified email at columbia.edu
Yibo ZengColumbia UniversityVerified email at columbia.edu

Hongseok Namkoong

Columbia University

Verified email at columbia.edu - Homepage

Operations Research Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Certifying some distributional robustness with principled adversarial training A Sinha, H Namkoong, R Volpi, J Duchi arXiv preprint arXiv:1710.10571, 2017	1181	2017
Generalizing to unseen domains via adversarial data augmentation R Volpi, H Namkoong, O Sener, JC Duchi, V Murino, S Savarese Advances in neural information processing systems 31, 2018	901	2018
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time M Wortsman, G Ilharco, SY Gadre, R Roelofs, R Gontijo-Lopes, ... International conference on machine learning, 23965-23998, 2022	858	2022
Fairness without demographics in repeated loss minimization T Hashimoto, M Srivastava, H Namkoong, P Liang International Conference on Machine Learning, 1929-1938, 2018	696	2018
Robust fine-tuning of zero-shot models M Wortsman, G Ilharco, JW Kim, M Li, S Kornblith, R Roelofs, RG Lopes, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022	638	2022
Learning models with uniform performance via distributionally robust optimization J Duchi, H Namkoong Annals of Statistics 49 (3), 1378-1406, 2021	450	2021
Variance-based regularization with convex objectives J Duchi, H Namkoong Journal of Machine Learning Research 20 (68), 1-55, 2019	408	2019
Statistics of robust optimization: A generalized empirical likelihood approach J Duchi, P Glynn, H Namkoong Mathematics of Operations Research 46 (3), 946-969, 2021	395	2021
Stochastic gradient methods for distributionally robust optimization with f-divergences H Namkoong, JC Duchi Advances in neural information processing systems 29, 2016	373	2016
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation M O'Kelly, A Sinha, H Namkoong, J Duchi, R Tedrake Advances in Neural Information Processing Systems, 2018	280	2018
Openclip G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ...	274	2021
Openclip, July 2021 G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ... URL https://doi. org/10.5281/zenodo 5143773, 29, 0	254
Distributionally robust losses for latent covariate mixtures J Duchi, T Hashimoto, H Namkoong Operations Research 71 (2), 649-664, 2023	171*	2023
Openclip, 2021 G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ... If you use this software, please cite it as below 3 (5), 0	117
Bounds on the conditional and average treatment effect with unobserved confounding factors S Yadlowsky, H Namkoong, S Basu, J Duchi, L Tian Annals of Statistics 50 (5), 2587-2615, 2022	99*	2022
Off-policy policy evaluation for sequential decisions under unobserved confounding H Namkoong, R Keramati, S Yadlowsky, E Brunskill Advances in Neural Information Processing Systems 33, 18819-18831, 2020	76	2020
Adaptive sampling probabilities for non-smooth optimization H Namkoong, A Sinha, S Yadlowsky, JC Duchi International Conference on Machine Learning, 2574-2583, 2017	46	2017
Assessing External Validity Over Worst-case Subpopulations S Jeong, H Namkoong Conference on Learning Theory, 2079-2084, 2020	35*	2020
Diagnosing model performance under distribution shift TT Cai, H Namkoong, S Yadlowsky arXiv preprint arXiv:2303.02011, 2023	25	2023
Evaluating model performance under worst-case subpopulations M Li, H Namkoong, S Xia Advances in Neural Information Processing Systems 34, 17325-17334, 2021	21	2021

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