In this paper, we focus on the case of nonconvex losses. Classical empirical process theory implies uniform convergence of the empirical (or sample) risk to the population risk. While under additional ...

A distributed multiagent deep reinforcement learning algorithm (DMADRLA) with theoretical guarantees is proposed for the distributed nonconvex constraint optimization problem. This algorithm provides ...

A swarm-exploring neurodynamic network (SENN) based on a two-timescale model is proposed in this study for solving nonconvex nonlinear programming problems. First, by using a convergent-differential ...