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...
State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translat...
Jorge Civera, Elsa Cubel, Antonio L. Lagarda, Davi...
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
: This paper presents a proposal to tackle the design and development of user interfaces for groupware applications. This proposal includes important design and implementation issu...
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...