Hongseok Namkoong
Hongseok Namkoong
columbia.edu üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Alıntı yapanlar
Alıntı yapanlar
Certifying Some Distributional Robustness with Principled Adversarial Training
A Sinha, H Namkoong, J Duchi
International Conference on Learning Representations, 2018
Generalizing to unseen domains via adversarial data augmentation
R Volpi, H Namkoong, O Sener, J Duchi, V Murino, S Savarese
arXiv preprint arXiv:1805.12018, 2018
Fairness without demographics in repeated loss minimization
T Hashimoto, M Srivastava, H Namkoong, P Liang
International Conference on Machine Learning, 1929-1938, 2018
Variance-based regularization with convex objectives
J Duchi, H Namkoong
The Journal of Machine Learning Research 20 (1), 2450-2504, 2019
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences.
H Namkoong, JC Duchi
NIPS 29, 2208-2216, 2016
Statistics of robust optimization: A generalized empirical likelihood approach
JC Duchi, PW Glynn, H Namkoong
Mathematics of Operations Research, 2021
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
Learning models with uniform performance via distributionally robust optimization
JC Duchi, H Namkoong
The Annals of Statistics 49 (3), 1378-1406, 2021
Distributionally robust losses for latent covariate mixtures
J Duchi, T Hashimoto, H Namkoong
arXiv preprint arXiv:2007.13982, 2020
Adaptive sampling probabilities for non-smooth optimization
H Namkoong, A Sinha, S Yadlowsky, JC Duchi
International Conference on Machine Learning, 2574-2583, 2017
Bounds on the conditional and average treatment effect in the presence of unobserved confounders
S Yadlowsky, H Namkoong, S Basu, J Duchi, L Tian
arXiv preprint arXiv:1808.09521, 2018
Off-policy policy evaluation for sequential decisions under unobserved confounding
H Namkoong, R Keramati, S Yadlowsky, E Brunskill
arXiv preprint arXiv:2003.05623, 2020
Robust fine-tuning of zero-shot models
M Wortsman, G Ilharco, M Li, JW Kim, H Hajishirzi, A Farhadi, ...
arXiv preprint arXiv:2109.01903, 2021
Robust causal inference under covariate shift via worst-case subpopulation treatment effects
S Jeong, H Namkoong
Conference on Learning Theory, 2079-2084, 2020
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning
H Namkoong, S Daulton, E Bakshy
arXiv preprint arXiv:2011.14266, 2020
In-silico risk analysis of personalized artificial pancreas controllers via rare-event simulation
M O'Kelly, A Sinha, J Norden, H Namkoong
arXiv preprint arXiv:1812.00293, 2018
Evaluating model performance under worst-case subpopulations
M Li, H Namkoong, S Xia
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
Lecture 4: Distributional Robustness
H Namkoong
Reliable Machine Learning via Distributional Robustness
H Namkoong
Stanford University, 2019
Proofs for empirical likelihood with general f-divergences
H Namkoong, JC Duchi, PW Glynn
Sistem, işlemi şu anda gerçekleştiremiyor. Daha sonra yeniden deneyin.
Makaleler 1–20