Jun, Kwang-Sung

34 publications

ICML 2025 Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification Kapilan Balagopalan, Ngo Tuan Nguyen, Yao Zhao, Kwang-Sung Jun

AISTATS 2025 HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search Tuan Nguyen, Jay Barrett, Kwang-Sung Jun

COLT 2025 Improved Offline Contextual Bandits with Second-Order Bounds: Betting and Freezing J. Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun

AISTATS 2025 Minimum Empirical Divergence for Sub-Gaussian Linear Bandits Kapilan Balagopalan, Kwang-Sung Jun

NeurIPS 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Jungyhun Lee, Se-Young Yun, Kwang-Sung Jun

ICMLW 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee, Se-Young Yun, Kwang-Sung Jun

NeurIPS 2024 Adaptive Experimentation When You Can't Experiment Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain

COLT 2024 Better-than-KL PAC-Bayes Bounds Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona

ICML 2024 Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun

AISTATS 2024 Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion Junghyun Lee, Se-Young Yun, Kwang-Sung Jun

ICML 2024 Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization Kwang-Sung Jun, Jungtaek Kim

NeurIPS 2023 Kullback-Leibler Maillard Sampling for Multi-Armed Bandits with Bounded Rewards Hao Qin, Kwang-Sung Jun, Chicheng Zhang

ICML 2023 Revisiting Simple Regret: Fast Rates for Returning a Good Arm Yao Zhao, Connor Stephens, Csaba Szepesvari, Kwang-Sung Jun

COLT 2023 Tighter PAC-Bayes Bounds Through Coin-Betting Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona

AISTATS 2022 Jointly Efficient and Optimal Algorithms for Logistic Bandits Louis Faury, Marc Abeille, Kwang-Sung Jun, Clement Calauzenes

AISTATS 2022 Maillard Sampling: Boltzmann Exploration Done Optimally Jie Bian, Kwang-Sung Jun

AISTATS 2022 Norm-Agnostic Linear Bandits Spencer B. Gales, Sunder Sethuraman, Kwang-Sung Jun

AAAI 2022 An Experimental Design Approach for Regret Minimization in Logistic Bandits Blake Mason, Kwang-Sung Jun, Lalit Jain

NeurIPS 2022 Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs Yeoneung Kim, Insoon Yang, Kwang-Sung Jun

NeurIPS 2022 PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun

ICML 2021 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif

ICML 2021 Improved Regret Bounds of Bilinear Bandits Using Action Space Analysis Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang

NeurIPS 2020 Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality Kwang-Sung Jun, Chicheng Zhang

ICML 2019 Bilinear Bandits with Low-Rank Structure Kwang-Sung Jun, Rebecca Willett, Stephen Wright, Robert Nowak

NeurIPS 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona

COLT 2019 Parameter-Free Online Convex Optimization with Sub-Exponential Noise Kwang-Sung Jun, Francesco Orabona

NeurIPS 2018 Adversarial Attacks on Stochastic Bandits Kwang-Sung Jun, Lihong Li, Yuzhe Ma, Xiaojin Zhu

AISTATS 2017 Improved Strongly Adaptive Online Learning Using Coin Betting Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett

NeurIPS 2017 Scalable Generalized Linear Bandits: Online Computation and Hashing Kwang-Sung Jun, Aniruddha Bhargava, Robert Nowak, Rebecca Willett

ICML 2016 Anytime Exploration for Multi-Armed Bandits Using Confidence Information Kwang-Sung Jun, Robert Nowak

AISTATS 2016 Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls Kwang-Sung Jun, Kevin G. Jamieson, Robert D. Nowak, Xiaojin Zhu

NeurIPS 2015 Human Memory Search as Initial-Visit Emitting Random Walk Kwang-Sung Jun, Xiaojin Zhu, Timothy T. Rogers, Zhuoran Yang, Ming Yuan

ICML 2013 Learning from Human-Generated Lists Kwang-Sung Jun, Jerry Zhu, Burr Settles, Timothy Rogers

ICML 2010 Cognitive Models of Test-Item Effects in Human Category Learning Xiaojin Zhu, Bryan R. Gibson, Kwang-Sung Jun, Timothy T. Rogers, Joseph Harrison, Chuck Kalish