← Authors

Hongseok Namkoong

18 papers · 2016–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (9) πŸ—ΊοΈ Taxonomy Completionist (37) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌍 Conference Polyglot (6) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ’Ž Century Club (18) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (82) πŸ”₯ Unstoppable (10)

Conferences

NIPS (9) ICML (4) ICLR (2) COLT (1) CVPR (1) JMLR (1)

Top co-authors

John C. Duchi (5) Aman Sinha (3) Steve Yadlowsky (2) Mike Li (2) Mitchell Wortsman (2) Simon Kornblith (2) Gabriel Ilharco (2) Rebecca Roelofs (2) John Duchi (2) Ali Farhadi (2)

Research topics

Applications (1)

Keywords

distributionally robust optimization (4) distribution shift (3) domain generalization (2) model ensemble (2) domain adaptation (2) stochastic gradient descent (2) covariate shift (2) empirical risk minimization (2) variance regularization (2) empirical likelihood (2) risk minimization (2) causal inference (2) transfer learning (1) policy optimization (1) risk management (1) reinforcement learning (1) active learning (1) robust optimization (1) data augmentation (1) adversarial learning (1)

Papers

PersonalLLM: Tailoring LLMs to Individual Preferences ICLR 2025
Adaptive Elicitation of Latent Information Using Natural Language ICML 2025
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation NIPS 2024
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers NIPS 2024
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets NIPS 2023
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time ICML 2022
Robust Fine-Tuning of Zero-Shot Models CVPR 2022
Evaluating model performance under worst-case subpopulations NIPS 2021
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding NIPS 2020
Robust causal inference under covariate shift via worst-case subpopulation treatment effects COLT 2020
Variance-based Regularization with Convex Objectives JMLR 2019
Fairness Without Demographics in Repeated Loss Minimization ICML 2018
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation NIPS 2018
Certifying Some Distributional Robustness with Principled Adversarial Training ICLR 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation NIPS 2018
Adaptive Sampling Probabilities for Non-Smooth Optimization ICML 2017
Variance-based Regularization with Convex Objectives NIPS 2017
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NIPS 2016