Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...