1 citations · 1 across the 4 of their papers we have counts for
4 papers
Small-Covariance Noise-to-State Stability of Stochastic Systems and Its Applications to Stochastic Gradient Dynamics
Leilei Cui, Zhong-Ping Jiang, Eduardo D. Sontag
This paper studies gradient dynamics subject to additive random noise, which may arise from sources such as stochastic gradient estimation, measurement noise, or stochastic samplin…
Perturbed Gradient Descent Algorithms are Small-Disturbance Input-to-State Stable
Leilei Cui, Zhong-Ping Jiang, Eduardo D. Sontag +1
This article investigates the robustness of gradient descent algorithms under perturbations. The concept of small-disturbance input-to-state stability (ISS) for discrete-time nonli…
A Fully Data-Driven Value Iteration for Stochastic LQR: Convergence, Robustness and Stability
Leilei Cui, Zhong-Ping Jiang, Petter N. Kolm +1
Unlike traditional model-based reinforcement learning approaches that estimate system parameters from data, non-model-based data-driven control learns the optimal policy directly f…
Small-Disturbance Input-to-State Stability of Perturbed Gradient Flows: Applications to LQR Problem
Leilei Cui, Zhong-Ping Jiang, Eduardo D. Sontag
This paper studies the effect of perturbations on the gradient flow of a general nonlinear programming problem, where the perturbation may arise from inaccurate gradient estimation…