COLT

Second-Order Bounds for [0,1]-Valued Regression via Betting Loss

Yinan Li, Sungjoon Yoon, Ethan Huang, Kwang-Sung Jun

Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning

Harin Lee, Min-hwan Oh

Experimental Design for Semiparametric Bandits

Seok-Jin Kim, Gi-Soo Kim, Min-hwan Oh

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

J. Jon Ryu, Jeongyeol Kwon, Benjamin Koppe, Kwang-Sung Jun Jun

Better-than-KL PAC-Bayes Bounds

Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona

Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds

Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh

Tighter PAC-Bayes bounds through coin-betting

Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona