Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
The modeling of high level semantic events from low level sensor signals is important in order to understand distributed phenomena. For such content-modeling purposes, transformat...
Transactional Memory (TM) is considered as one of the most promising paradigms for developing concurrent applications. TM has been shown to scale well on multiple cores when the d...
Walther Maldonado, Patrick Marlier, Pascal Felber,...
The task of computing molecular structure from combinations of experimental and theoretical constraints is expensive because of the large number of estimated parameters (the 3D co...
Cheng Che Chen, Jaswinder Pal Singh, Russ B. Altma...
Background estimation and removal based on the joint use of range and color data produces superior results than can be achieved with either data source alone. This is increasingly...
Gaile G. Gordon, Trevor Darrell, Michael Harville,...