We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory ...
A scalable podcast solution developed at the University of Washington makes the podcasting of class lectures easy for faculty by automating the capture, uploading, and delivery of...
Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this w...
Abstract. This paper addresses the problem of how to learn an appropriate feature representation from video to benefit video-based face recognition. By simultaneously exploiting th...