The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Remote sensing based on imagery has traditionally been the main tool used to extract land uses and land cover (LULC) maps. However, more powerful tools are needed in order to fulfi...
This paper contributes and evaluates a model and a methodology for implementing parallel wavefront algorithms on the Cell Broadband Engine. Wavefront algorithms are vital in sever...
Ashwin M. Aji, Wu-chun Feng, Filip Blagojevic, Dim...
ng precision of abstract SystemC models using the SystemC Verification Standard Franco Carbognani1 , Christopher K. Lennard2 , C. Norris Ip3 , Allan Cochrane2 , Paul Bates2 1 Caden...
Franco Carbognani, Christopher K. Lennard, C. Norr...