4 citations · 10 across the 13 of their papers we have counts for
5 papers · 1 filter
Scalable spectral representations for multi-agent reinforcement learning in network MDPs
Zhaolin Ren, Runyu Zhang, Bo Dai +1
Network Markov Decision Processes (MDPs), a popular model for multi-agent control, pose a significant challenge to efficient learning due to the exponential growth of the global st…
Distributed Thompson sampling under constrained communication
Saba Zerefa, Zhaolin Ren, Haitong Ma +1
In Bayesian optimization, a black-box function is maximized via the use of a surrogate model. We apply distributed Thompson sampling, using a Gaussian process as a surrogate model,…
Enhancing Preference-based Linear Bandits via Human Response Time
Shen Li, Yuyang Zhang, Zhaolin Ren +3
Interactive preference learning systems infer human preferences by presenting queries as pairs of options and collecting binary choices. Although binary choices are simple and wide…
Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
Haitong Ma, Zhaolin Ren, Bo Dai +1
We study sim-to-real skill transfer and discovery in the context of robotics control using representation learning. We draw inspiration from spectral decomposition of Markov decisi…
TS-RSR: A provably efficient approach for batch Bayesian Optimization
Zhaolin Ren, Na Li
This paper presents a new approach for batch Bayesian Optimization (BO) called Thompson Sampling-Regret to Sigma Ratio directed sampling (TS-RSR), where we sample a new batch of ac…