A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendri...
The aim of the project we discuss in this paper is to develop a computational model of peer learning. We present an extensive analysis of peer learning dialogues, analysis on which...
Cynthia Kersey, Barbara Di Eugenio, Pamela W. Jord...
A number of natural models for learning in the limit is introduced to deal with the situation when a learner is required to provide a grammar covering the input even if only a par...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...