Kwang-Sung Jun

IEEE Trans. Inf. Theory, January, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

Junghyun Lee

Se-Young Yun

CoRR, 2024

Adaptive Experimentation When You Can't Experiment.

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

Jungtaek Kim

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

[BibT_eX]

[DOI]

Kyoungseok Jang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Better-than-KL PAC-Bayes Bounds.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

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

[BibT_eX]

[DOI]

Junghyun Lee

Se-Young Yun

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Graph Sparsifications using Neural Network Assisted Monte Carlo Tree Search.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Hao Qin

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Tighter PAC-Bayes Bounds Through Coin-Betting.

[BibT_eX]

[DOI]

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Revisiting Simple Regret Minimization in Multi-Armed Bandits.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

Yeoneung Kim

Insoon Yang

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.

[BibT_eX]

[DOI]

Kyoungseok Jang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Norm-Agnostic Linear Bandits.

[BibT_eX]

[DOI]

Spencer B. Gales

Sunder Sethuraman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Jointly Efficient and Optimal Algorithms for Logistic Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Maillard Sampling: Boltzmann Exploration Done Optimally.

[BibT_eX]

[DOI]

Jie Bian

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

An Experimental Design Approach for Regret Minimization in Logistic Bandits.

[BibT_eX]

[DOI]

Blake Mason

Lalit Jain

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

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

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

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

[BibT_eX]

[DOI]

Lalit Jain

Houssam Nassif

CoRR, 2020

Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

Ashok Cutkosky

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.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Parameter-Free Online Convex Optimization with Sub-Exponential Noise.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

2018

Adversarial Attacks on Stochastic Bandits.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Decision and Game Theory for Security - 9th International Conference, 2018

2017

Online Learning for Changing Environments using Coin Betting.

[BibT_eX]

[DOI]

CoRR, 2017

Scalable Generalized Linear Bandits: Online Computation and Hashing.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Xiaozhu Meng

Barton P. Miller

Proceedings of the Computer Security - ESORICS 2017, 2017

Improved Strongly Adaptive Online Learning using Coin Betting.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Anytime Exploration for Multi-armed Bandits using Confidence Information.

[BibT_eX]

[DOI]

Robert D. Nowak

Proceedings of the 33nd International Conference on Machine Learning, 2016

Graph-based active learning: A new look at expected error minimization.

[BibT_eX]

[DOI]