We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
We propose a frame structure that is augmented with belief functions to model knowledge in a spoken dialog system. In addition we propose methods to combine belief functions in the...
Abstract. In the future it is likely that peer communities will be routinely established for the purpose of sharing electronic resources and targeted information among groups of pe...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...