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JMLR
2010
139views more  JMLR 2010»
15 years 1 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
IJON
2011
90views more  IJON 2011»
14 years 10 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
COMSUR
2011
228views Hardware» more  COMSUR 2011»
14 years 6 months ago
Energy Harvesting Sensor Nodes: Survey and Implications
Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-har...
Sujesha Sudevalayam, Purushottam Kulkarni
WOSP
2004
ACM
16 years 9 days ago
Early performance testing of distributed software applications
Performance characteristics, such as response time, throughput and scalability, are key quality attributes of distributed applications. Current practice, however, rarely applies s...
Giovanni Denaro, Andrea Polini, Wolfgang Emmerich
MM
2003
ACM
146views Multimedia» more  MM 2003»
16 years 3 days ago
Supporting timeliness and accuracy in distributed real-time content-based video analysis
Real-time content-based access to live video data requires content analysis applications that are able to process the video data at least as fast as the video data is made availab...
Viktor S. Wold Eide, Frank Eliassen, Ole-Christoff...