5 citations · 9 across the 3 of their papers we have counts for
3 papers
Optimal Rate of Convergence for Quasi-Stochastic Approximation
Andrey Bernstein, Yue Chen, Marcello Colombino +3
The Robbins-Monro stochastic approximation algorithm is a foundation of many algorithmic frameworks for reinforcement learning (RL), and often an efficient approach to solving (or…
Feedback Particle Filter on Matrix Lie Groups
Chi Zhang, Amirhossein Taghvaei, Prashant G. Mehta
This paper is concerned with the problem of continuous-time nonlinear filtering for stochastic processes on a connected matrix Lie group. The main contribution of this paper is to…
A Controlled Particle Filter for Global Optimization
Chi Zhang, Amirhossein Taghvaei, Prashant G. Mehta
A particle filter is introduced to numerically approximate a solution of the global optimization problem. The theoretical significance of this work comes from its variational aspec…