متابعة
Hongseok Namkoong
Hongseok Namkoong
Columbia University
بريد إلكتروني تم التحقق منه على columbia.edu - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Certifying some distributional robustness with principled adversarial training‏
A Sinha, H Namkoong, R Volpi, J Duchi‏
arXiv preprint arXiv:1710.10571, 2017‏
12012017
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
9362018
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
9322022
Fairness without demographics in repeated loss minimization‏
T Hashimoto, M Srivastava, H Namkoong, P Liang‏
International Conference on Machine Learning, 1929-1938, 2018‏
7172018
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
6842022
Learning models with uniform performance via distributionally robust optimization‏
J Duchi, H Namkoong‏
Annals of Statistics 49 (3), 1378-1406, 2021‏
4692021
Variance-based regularization with convex objectives‏
J Duchi, H Namkoong‏
Journal of Machine Learning Research 20 (68), 1-55, 2019‏
4192019
Statistics of robust optimization: A generalized empirical likelihood approach‏
J Duchi, P Glynn, H Namkoong‏
Mathematics of Operations Research 46 (3), 946-969, 2021‏
4072021
Stochastic gradient methods for distributionally robust optimization with f-divergences‏
H Namkoong, JC Duchi‏
Advances in neural information processing systems 29, 2016‏
3862016
Openclip‏
G Ilharco, M Wortsman, R Wightman, C Gordon, N Carlini, R Taori, ...‏
3012021
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
2882018
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
266
Distributionally robust losses for latent covariate mixtures‏
J Duchi, T Hashimoto, H Namkoong‏
Operations Research 71 (2), 649-664, 2023‏
176*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
126
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
103*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
812020
Adaptive sampling probabilities for non-smooth optimization‏
H Namkoong, A Sinha, S Yadlowsky, JC Duchi‏
International Conference on Machine Learning, 2574-2583, 2017‏
472017
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
322023
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, 2024‏
272024
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مقالات 1–20