Kwang-Sung Jun

33 papers · 2012–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (30) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🏃 Academic Marathon (13) 🔬 Deep Specialist (14) 🏆 Keyword Champion (3) 🗃️ Keyword Collector (102) 🚀 Conference Pioneer 💎 Century Club (33) 🔥 Unstoppable (11) 📈 Trend Setter ⚡ Prolific Year (6)

Conferences

NIPS (10) ICML (9) AISTATS (8) COLT (4) AAAI (1) NAACL (1)

Top co-authors

Kyoungseok Jang (5) Francesco Orabona (5) Robert Nowak (4) Chicheng Zhang (4) Xiaojin Zhu (4) Rebecca Willett (3) Se-Young Yun (3) Yao Zhao (3) Lalit Jain (3) Kapilan Balagopalan (2)

Keywords

regret bound (14) multi-armed bandit (8) online learning (7) logistic bandit (4) pure exploration (4) confidence bound (3) thompson sampling (3) linear bandit (3) experimental design (3) regret minimization (3) coin betting (2) bilinear bandit (2) confidence set (2) confidence sequence (2) pac-bayes bound (2) stochastic bandit (2) asymptotic optimality (2) stochastic optimization (2) maximum likelihood estimation (2) posterior distribution (1)

Papers

HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search AISTATS 2025

Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification ICML 2025

Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing COLT 2025

Minimum Empirical Divergence for Sub-Gaussian Linear Bandits AISTATS 2025

Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization ICML 2024

Adaptive Experimentation When You Can't Experiment NIPS 2024

A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits NIPS 2024

Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion AISTATS 2024

Better-than-KL PAC-Bayes Bounds COLT 2024

Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits ICML 2024

Revisiting Simple Regret: Fast Rates for Returning a Good Arm ICML 2023

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards NIPS 2023

Tighter PAC-Bayes Bounds Through Coin-Betting COLT 2023

Jointly Efficient and Optimal Algorithms for Logistic Bandits AISTATS 2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits AAAI 2022

Maillard Sampling: Boltzmann Exploration Done Optimally AISTATS 2022

Norm-Agnostic Linear Bandits AISTATS 2022

Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs NIPS 2022

PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits NIPS 2022

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis ICML 2021

Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits ICML 2021

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality NIPS 2020

Parameter-Free Online Convex Optimization with Sub-Exponential Noise COLT 2019

Bilinear Bandits with Low-rank Structure ICML 2019

Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NIPS 2019

Adversarial Attacks on Stochastic Bandits NIPS 2018

Improved Strongly Adaptive Online Learning using Coin Betting AISTATS 2017

Scalable Generalized Linear Bandits: Online Computation and Hashing NIPS 2017

Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls AISTATS 2016

Anytime Exploration for Multi-armed Bandits using Confidence Information ICML 2016

Human Memory Search as Initial-Visit Emitting Random Walk NIPS 2015

Learning from Human-Generated Lists ICML 2013

Learning from Bullying Traces in Social Media NAACL 2012