Effective modeling and management of hardware resources have always been critical toward generating highly efficient code in static compilers. With Just-In-Time compilation and dy...
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
—The objective of this paper is to study how algorithms of optimization affect the parametersestimation of Autoregressive AR(1)Models. In our research we have represented the AR...
Abstract. We consider the solution of a (generalized) eigenvalue problem arising in physical oceanography that involves the evaluation of both the tangent-linear and adjoint versio...
In this paper we describe a method to learn parameters
which govern pedestrian motion by observing video
data. Our learning framework is based on variational
mode learning and a...