4 papers
Physics-Informed Parametric Bandits for Beam Alignment in mmWave Communications
Hao Qin, Thang Duong, Ming F. Li +1
In millimeter wave (mmWave) communications, beam alignment and tracking are crucial to combat the significant path loss. As scanning the entire directional space is inefficient, de…
Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
Zhi Wang, Chicheng Zhang, Ramya Korlakai Vinayak
In lifelong learning, a learner faces a sequence of tasks with shared structure and aims to identify and leverage it to accelerate learning. We study the setting where such structu…
Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM
Thang Duong, Minglai Yang, Chicheng Zhang
We investigate the usage of Large Language Model (LLM) in collecting high-quality data to warm-start Reinforcement Learning (RL) algorithms for learning in some classical Markov De…
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits
Thang Duong, Zhi Wang, Chicheng Zhang
We study lifelong learning in linear bandits, where a learner interacts with a sequence of linear bandit tasks whose parameters lie in an -dimensional subspace of …