Hongseok Namkoong
18 papers · 2016–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (6) 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🏃 Academic Marathon (9)
🐣
Hot Topic Early Bird
🐝
Cross-Pollinator
(10)
🌍
Conference Polyglot
(6)
👑
Triple Crown
🏆
Keyword Champion
(2)
💎
Century Club
(18)
📈
Trend Setter
🚀
Conference Pioneer
🗃️
Keyword Collector
(82)
🔥
Unstoppable
(10)
Conferences
NIPS (9)
ICML (4)
ICLR (2)
COLT (1)
CVPR (1)
JMLR (1)
Top co-authors
Research topics
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