Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
Overlay topologies are now popular with many emerging peer-to-peer (P2P) systems, to efficiently locate and retrieve information. In contrast, the focus of this work is to use ove...
In this paper, we assess the impact of heterogeneity on scheduling independent tasks on master-slave platforms. We assume a realistic one-port model where the master can communica...