Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
The unsplittable flow problem is one of the most extensively studied optimization problems in the field of networking. An instance of it consists of an edge capacitated graph and ...
The set of frames exchanged in automotive applications must meet two constraints: it has to be feasible from a schedulability point of view and it should minimize the network bandw...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...