The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 200...
Autocalibration is a difficult problem. Not only is its computation very noisesensitive, but there also exist many critical motions that prevent the estimation of some of the came...
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
Double Patterning Lithography (DPL) is one of the few hopeful candidate solutions for the lithography for CMOS process beyond 45nm. DPL assigns the patterns less than a certain di...