1 citations · 1 across the 8 of their papers we have counts for
8 papers
DER Allocation without Load Prediction via Reinforcement Learning
Abed AlRahman Al Makdah, Aravind Ramana, Shaofeng Zou +2
The growing variability of renewable generation increases the need for fast and flexible grid-balancing mechanisms. Existing frameworks for distributed energy resource aggregations…
Hopf bifurcations in a reaction-diffusion model with a general advection term and delay effect
Jingxiao Song, Chengwei Ren, Shaofen Zou
This paper investigates a class of reaction-diffusion population models defined on a bounded domain, characterized by a general time-delayed per capita growth rate and a general ad…
Linear Dynamics meets Linear MDPs: Closed-Form Optimal Policies via Reinforcement Learning
Abed AlRahman Al Makdah, Oliver Kosut, Lalitha Sankar +1
Many applications -- including power systems, robotics, and economics -- involve a dynamical system interacting with a stochastic and hard-to-model environment. We adopt a reinforc…
Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model
Zilong Deng, Simon Khan, Shaofeng Zou
In this work, we study the sample complexity problem of risk-sensitive Reinforcement Learning (RL) with a generative model, where we aim to maximize the Conditional Value at Risk (…
Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization
Yufeng Yang, Erin Tripp, Yifan Sun +2
Recent studies have shown that many nonconvex machine learning problems satisfy a generalized-smooth condition that extends beyond traditional smooth nonconvex optimization. Howeve…
Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
Yudan Wang, Yue Wang, Yi Zhou +1
Actor-critic (AC) is a powerful method for learning an optimal policy in reinforcement learning, where the critic uses algorithms, e.g., temporal difference (TD) learning with func…
Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance
Qi Zhang, Yi Zhou, Shaofeng Zou
This paper provides the first tight convergence analyses for RMSProp and Adam in non-convex optimization under the most relaxed assumptions of coordinate-wise generalized smoothnes…
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Ashley Prater-Bennette +2
Distributionally robust optimization (DRO) is a powerful framework for training robust models against data distribution shifts. This paper focuses on constrained DRO, which has an…