Kwang-Sung Jun

Orcid: 0000-0001-5483-3161

According to our database1, Kwang-Sung Jun authored at least 40 papers between 2010 and 2024.

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Bibliography

2024
Tight Concentrations and Confidence Sequences From the Regret of Universal Portfolio.
IEEE Trans. Inf. Theory, January, 2024

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

Better-than-KL PAC-Bayes Bounds.
CoRR, 2024

Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization.
CoRR, 2024

2023
Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search.
CoRR, 2023

Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion.
CoRR, 2023

Nearly Optimal Steiner Trees using Graph Neural Network Assisted Monte Carlo Tree Search.
CoRR, 2023

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting Simple Regret: Fast Rates for Returning a Good Arm.
Proceedings of the International Conference on Machine Learning, 2023

Tighter PAC-Bayes Bounds Through Coin-Betting.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Revisiting Simple Regret Minimization in Multi-Armed Bandits.
CoRR, 2022

Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Norm-Agnostic Linear Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Jointly Efficient and Optimal Algorithms for Logistic Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Maillard Sampling: Boltzmann Exploration Done Optimally.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Transfer Learning in Bandits with Latent Continuity.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Improved Confidence Bounds for the Linear Logistic Model and Applications to Linear Bandits.
CoRR, 2020

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Parameter-Free Locally Differentially Private Stochastic Subgradient Descent.
CoRR, 2019

Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bilinear Bandits with Low-rank Structure.
Proceedings of the 36th International Conference on Machine Learning, 2019

Parameter-Free Online Convex Optimization with Sub-Exponential Noise.
Proceedings of the Conference on Learning Theory, 2019

2018
Adversarial Attacks on Stochastic Bandits.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Data Poisoning Attacks in Contextual Bandits.
Proceedings of the Decision and Game Theory for Security - 9th International Conference, 2018

2017
Online Learning for Changing Environments using Coin Betting.
CoRR, 2017

Scalable Generalized Linear Bandits: Online Computation and Hashing.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Identifying Multiple Authors in a Binary Program.
Proceedings of the Computer Security - ESORICS 2017, 2017

Improved Strongly Adaptive Online Learning using Coin Betting.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Anytime Exploration for Multi-armed Bandits using Confidence Information.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Graph-based active learning: A new look at expected error minimization.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

U-INVITE: Estimating Individual Semantic Networks from Fluency Data.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Human Memory Search as Initial-Visit Emitting Random Walk.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013
Learning from Human-Generated Lists.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Learning from Bullying Traces in Social Media.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2012

2010
Cognitive Models of Test-Item Effects in Human Category Learning.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


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