This paper presents a novel prototype hierarchy based clustering (PHC) framework for the organization of web collections. It solves simultaneously the problem of categorizing web ...
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Abstract— For the past decade or so, evolutionary multiobjective optimization (EMO) methodologies have earned wide popularity for solving complex practical optimization problems,...
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...