5 papers
A Min-Max Gradient Search Method for Constrained Simulation Optimization
Ruiyang Jin, Siyang Gao, Henry Lam
Constrained simulation optimization (CSO) is a general framework for optimizing stochastic systems under performance constraints. It arises widely in practice where objective and c…
Query-Efficient Zeroth-Order Algorithms for Nonconvex Constrained Optimization
Ruiyang Jin, Yuke Zhou, Yujie Tang +2
Zeroth-order optimization (ZO) has been a powerful framework for solving black-box problems, which estimates gradients using zeroth-order data to update variables iteratively. The…
A Zeroth-Order Extra-Gradient Method for Black-Box Constrained Optimization
Yuke Zhou, Ruiyang Jin, Siyang Gao +2
Non-analytical objectives and constraints often arise in control systems, particularly in problems with complex dynamics, which are challenging yet lack efficient solution methods.…
Approximate Global Convergence of Independent Learning in Multi-Agent Systems
Ruiyang Jin, Zaiwei Chen, Yiheng Lin +2
Independent learning (IL), despite being a popular approach in practice to achieve scalability in large-scale multi-agent systems, usually lacks global convergence guarantees. In t…
Zeroth-Order Feedback-Based Optimization for Distributed Demand Response
Ruiyang Jin, Yujie Tang, Jie Song
Distributed demand response is a typical distributed optimization problem that requires coordination among multiple agents to satisfy demand response requirements. However, existin…