1 citations · 2 across the 9 of their papers we have counts for
3 papers · 2 filters
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…
Remarks on the Polyak-Lojasiewicz inequality and the convergence of gradient systems
Arthur Castello B. de Oliveira, Leilei Cui, Eduardo D. Sontag
This work explores generalizations of the Polyak-Lojasiewicz inequality (PLI) and their implications for the convergence behavior of gradient flows in optimization problems. Motiva…