Sledovat
Hongseok Namkoong
Hongseok Namkoong
Columbia University
E-mailová adresa ověřena na: columbia.edu - Domovská stránka
Název
Citace
Citace
Rok
Certifying some distributional robustness with principled adversarial training
A Sinha, H Namkoong, R Volpi, J Duchi
arXiv preprint arXiv:1710.10571, 2017
12222017
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
10382022
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
9482018
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
7452022
Fairness without demographics in repeated loss minimization
T Hashimoto, M Srivastava, H Namkoong, P Liang
International Conference on Machine Learning, 1929-1938, 2018
7372018
Learning models with uniform performance via distributionally robust optimization
J Duchi, H Namkoong
Annals of Statistics 49 (3), 1378-1406, 2021
4802021
Openclip
G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ...
4602021
Variance-based regularization with convex objectives
J Duchi, H Namkoong
Journal of Machine Learning Research 20 (68), 1-55, 2019
4202019
Statistics of robust optimization: A generalized empirical likelihood approach
J Duchi, P Glynn, H Namkoong
Mathematics of Operations Research 46 (3), 946-969, 2021
4082021
Stochastic gradient methods for distributionally robust optimization with f-divergences
H Namkoong, JC Duchi
Advances in neural information processing systems 29, 2016
4062016
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
296*
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
2922018
Distributionally robust losses for latent covariate mixtures
J Duchi, T Hashimoto, H Namkoong
Operations Research 71 (2), 649-664, 2023
180*2023
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
105*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
882020
Adaptive sampling probabilities for non-smooth optimization
H Namkoong, A Sinha, S Yadlowsky, JC Duchi
International Conference on Machine Learning, 2574-2583, 2017
492017
Assessing External Validity Over Worst-case Subpopulations
S Jeong, H Namkoong
Conference on Learning Theory, 2079-2084, 2020
37*2020
Diagnosing model performance under distribution shift
TT Cai, H Namkoong, S Yadlowsky
arXiv preprint arXiv:2303.02011, 2023
332023
On the need for a language describing distribution shifts: Illustrations on tabular datasets
J Liu, T Wang, P Cui, H Namkoong
Advances in Neural Information Processing Systems 36, 51371-51408, 2023
312023
Evaluating model performance under worst-case subpopulations
M Li, H Namkoong, S Xia
Advances in Neural Information Processing Systems 34, 17325-17334, 2021
212021
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Články 1–20