555 citations · 2.5k across the 105 of their papers we have counts for
49 papers · 1 filter
Online Learning for Supervisory Switching Control
Haoyuan Sun, Ali Jadbabaie
We study supervisory switching control for partially-observed linear dynamical systems. The objective is to identify and deploy a suitable controller for the unknown system by peri…
A least-square method for non-asymptotic identification in linear switching control
Haoyuan Sun, Ali Jadbabaie
The focus of this paper is on linear system identification in the setting where it is known that the underlying partially-observed linear dynamical system lies within a finite coll…
Convex and Non-convex Optimization Under Generalized Smoothness
Haochuan Li, Jian Qian, Yi Tian +2
Classical analysis of convex and non-convex optimization methods often requires the Lipshitzness of the gradient, which limits the analysis to functions bounded by quadratics. Rece…
Convergence of Adam Under Relaxed Assumptions
Haochuan Li, Alexander Rakhlin, Ali Jadbabaie
In this paper, we provide a rigorous proof of convergence of the Adaptive Moment Estimate (Adam) algorithm for a wide class of optimization objectives. Despite the popularity and e…
Model Predictive Control via On-Policy Imitation Learning
Kwangjun Ahn, Zakaria Mhammedi, Horia Mania +2
In this paper, we leverage the rapid advances in imitation learning, a topic of intense recent focus in the Reinforcement Learning (RL) literature, to develop new sample complexity…
On Convergence of Gradient Descent Ascent: A Tight Local Analysis
Haochuan Li, Farzan Farnia, Subhro Das +1
Gradient Descent Ascent (GDA) methods are the mainstream algorithms for minimax optimization in generative adversarial networks (GANs). Convergence properties of GDA have drawn sig…