19 citations · 32 across the 7 of their papers we have counts for
14 papers
Hierarchical Meta-learning-based Adaptive Controller
Fengze Xie, Guanya Shi, Michael O'Connell +2
We study how to design learning-based adaptive controllers that enable fast and accurate online adaptation in changing environments. In these settings, learning is typically done d…
Optimal Exploration for Model-Based RL in Nonlinear Systems
Andrew Wagenmaker, Guanya Shi, Kevin Jamieson
Learning to control unknown nonlinear dynamical systems is a fundamental problem in reinforcement learning and control theory. A commonly applied approach is to first explore the e…
Active Representation Learning for General Task Space with Applications in Robotics
Yifang Chen, Yingbing Huang, Simon S. Du +2
Representation learning based on multi-task pretraining has become a powerful approach in many domains. In particular, task-aware representation learning aims to learn an optimal r…
Online Optimization with Feedback Delay and Nonlinear Switching Cost
Weici Pan, Guanya Shi, Yiheng Lin +1
We study a variant of online optimization in which the learner receives -round about hitting cost and there is a multi-step nonlinear switching cost,…
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems
Yiheng Lin, Yang Hu, Haoyuan Sun +3
We study predictive control in a setting where the dynamics are time-varying and linear, and the costs are time-varying and well-conditioned. At each time step, the controller rece…
Meta-Adaptive Nonlinear Control: Theory and Algorithms
Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell +2
We present an online multi-task learning approach for adaptive nonlinear control, which we call Online Meta-Adaptive Control (OMAC). The goal is to control a nonlinear system subje…