Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Compared to subthreshold leakage, dynamic power is normally much less sensitive to the process variation due to its approximately linear relation to the process parameters. Howeve...
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
Weld joint penetration control is a basic research topic in the welding research community. The authors propose using an innovative plasma arc welding process referred to as the q...
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show (1) how to appro...