IEEE

Leveraging Transfer Learning in Deep Reinforcement Learning for Solving Combinatorial Optimization Problems Under Uncertainty

Abstract: In recent years, addressing the inherent uncertainties within Combinatorial Optimization Problems (COPs) reveals the limitations of traditional optimization methods. Although these methods ...
IEEE

A Fixed-Time Proximal Gradient Neurodynamic Network With Time-Varying Coefficients for Composite Optimization Problems and Sparse Optimization Problems With Log-Sum Function

Abstract: This article presents a novel proximal gradient neurodynamic network (PGNN) for solving composite optimization problems (COPs). The proposed PGNN with time-varying coefficients can be ...
AOL

Nonprofits are solving 21st century problems—they need 21st century tech

AI is accelerating progress in almost every sector. But in the social sector, it’s exposing a gap. Despite playing a crucial role as the first line of defense for vulnerable communities, nonprofits ...