This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
A fundamental requirement for autonomic computing is to be able to automatically infer how human users react in similar contextual conditions. This paper examines the problem of a...
Nearchos Paspallis, Konstantinos Kakousis, George ...
Server applications with adaptive behaviors can adapt their functionality in response to environmental changes, and significantly reduce the on-going costs of system deployment an...