We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
This paper describes BoostMap, a method for efficient nearest neighbor retrieval under computationally expensive distance measures. Database and query objects are embedded into a v...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
The purpose of this paper is to re-address the vision of human-computer symbiosis as originally expressed by J.C.R. Licklider nearly a half-century ago and to argue for the releva...
This paper presents a low power driven synthesis framework for the unique class of nonregenerative Boolean Read-Once Functions (BROF). A two-pronged approach is adopted, where the...
Users perceive varying levels of utility for each different job completed by the cluster. Therefore, there is a need for existing cluster Resource Management Systems (RMS) to prov...