Better-than-KL PAC-Bayes Bounds

no code implementations • 14 Feb 2024 • Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona

In this paper, we consider the problem of proving concentration inequalities to estimate the mean of the sequence.

Inductive Bias

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

no code implementations • 1 Jun 2023 • Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang

Under each framework, we consider both joint differential privacy (JDP) and local differential privacy (LDP) models.

Multi-Armed Bandits reinforcement-learning

Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning

no code implementations • 16 Feb 2023 • Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal

This improvement is a key to the significant regret improvement in quantum reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

Quantum Heavy-tailed Bandits

no code implementations • 23 Jan 2023 • Yulian Wu, Chaowen Guan, Vaneet Aggarwal, Di Wang

In this paper, we study multi-armed bandits (MAB) and stochastic linear bandits (SLB) with heavy-tailed rewards and quantum reward oracle.

Multi-Armed Bandits

Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits

no code implementations • 4 Jun 2021 • Youming Tao, Yulian Wu, Peng Zhao, Di Wang

Finally, we establish the lower bound to show that the instance-dependent regret of our improved algorithm is optimal.

Multi-Armed Bandits