This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that consid...
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
Ambiguity of entity mentions and concept references is a challenge to mining text beyond surface-level keywords. We describe an effective method of disambiguating surface forms an...
Yiping Zhou, Lan Nie, Omid Rouhani-Kalleh, Flavian...
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...