Hongseok Namkoong
18 papers · 2016–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (39) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π
Keyword Champion
(2)
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Triple Crown
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Silver
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
ποΈ
Keyword Collector
(97)
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory
(12)
Learning Types Β· Machine Learning
(11)
Application Areas
(10)
Artificial Intelligence
(7)
Core AI
(6)
Mathematics & Optimization
(3)
Optimization
(3)
Deep Learning
(2)
Reinforcement Learning
(2)
Learning Paradigms
(2)
Learning Types Β· Deep Learning
(2)
Methods
(2)
Computer Vision
(1)
Natural Language Processing
(1)
Keywords
distributionally robust optimization
(5)
distribution shift
(3)
causal inference
(2)
confidence interval
(2)
uncertainty quantification
(2)
covariate shift
(2)
risk minimization
(2)
domain adaptation
(2)
variance regularization
(2)
model ensemble
(2)
large language model
(2)
empirical risk minimization
(2)
domain generalization
(2)
stochastic gradient descent
(2)
empirical likelihood
(2)
transfer learning
(1)
policy optimization
(1)
risk management
(1)
reinforcement learning
(1)
active learning
(1)
Papers
Adaptive Elicitation of Latent Information Using Natural Language
ICML 2025
PersonalLLM: Tailoring LLMs to Individual Preferences
ICLR 2025
Adaptive Labeling for Efficient Out-of-distribution Model Evaluation
NeurIPS 2024
QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers
NeurIPS 2024
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
NeurIPS 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
NeurIPS 2021
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding
NeurIPS 2020
Robust causal inference under covariate shift via worst-case subpopulation treatment effects
COLT 2020
Variance-based Regularization with Convex Objectives
JMLR 2019
Certifying Some Distributional Robustness with Principled Adversarial Training
ICLR 2018
Fairness Without Demographics in Repeated Loss Minimization
ICML 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation
NeurIPS 2018
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
NeurIPS 2018
Adaptive Sampling Probabilities for Non-Smooth Optimization
ICML 2017
Variance-based Regularization with Convex Objectives
NeurIPS 2017
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences
NeurIPS 2016