Concurrent and distributed systems have traditionally been modelled using nondeterministic transitions over configurations. The minism provides an abstraction over scheduling, net...
This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the nu...
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Parts-based recognition has been suggested for generalizing from few training views in categorization scenarios. In this paper we present the results of a comparative investigation...