4 citations · 10 across the 13 of their papers we have counts for
13 papers
Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations
Haitong Ma, Bo Dai, Zhaolin Ren +2
Limited data has become a major bottleneck in scaling up offline imitation learning (IL). In this paper, we propose enhancing IL performance under limited expert data by introducin…
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…
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
Zhaolin Ren, Tongzheng Ren, Haitong Ma +2
This paper proposes an approach, Spectral Dynamics Embedding Control (SDEC), to optimal control for nonlinear stochastic systems. This method reveals an infinite-dimensional featur…
On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds
Zhaolin Ren, Yang Zheng, Maryam Fazel +1
The problem of controller reduction has a rich history in control theory. Yet, many questions remain open. In particular, there exist very few results on the order reduction of gen…
FedDAR: Federated Domain-Aware Representation Learning
Aoxiao Zhong, Hao He, Zhaolin Ren +2
Cross-silo Federated learning (FL) has become a promising tool in machine learning applications for healthcare. It allows hospitals/institutions to train models with sufficient dat…
Escaping saddle points in zeroth-order optimization: the power of two-point estimators
Zhaolin Ren, Yujie Tang, Na Li
Two-point zeroth order methods are important in many applications of zeroth-order optimization, such as robotics, wind farms, power systems, online optimization, and adversarial ro…
Gradient play in stochastic games: stationary points, convergence, and sample complexity
Runyu Zhang, Zhaolin Ren, Na Li
We study the performance of the gradient play algorithm for stochastic games (SGs), where each agent tries to maximize its own total discounted reward by making decisions independe…
Zeroth-Order Feedback Optimization for Cooperative Multi-Agent Systems
Yujie Tang, Zhaolin Ren, Na Li
We study a class of cooperative multi-agent optimization problems, where each agent is associated with a local action vector and a local cost, and the goal is to cooperatively find…
LQR with Tracking: A Zeroth-order Approach and Its Global Convergence
Zhaolin Ren, Aoxiao Zhong, Na Li
There has been substantial recent progress on the theoretical understanding of model-free approaches to Linear Quadratic Regulator (LQR) problems. Much attention has been devoted t…