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» Algorithms for Large, Sparse Network Alignment Problems
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ICML
2008
IEEE
16 years 5 months ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio
MOBIHOC
2008
ACM
16 years 4 months ago
Finding popular categories for RFID tags
As RFID tags are increasingly attached to everyday items, it quickly becomes impractical to collect data from every tag in order to extract useful information. In this paper, we c...
Bo Sheng, Chiu Chiang Tan, Qun Li, Weizhen Mao
INFOCOM
2011
IEEE
14 years 7 months ago
A comparative study of two network-based anomaly detection methods
—Modern networks are complex and hence, network operators often rely on automation to assist in assuring the security, availability, and performance of these networks. At the cor...
Kaustubh Nyalkalkar, Sushant Sinha, Michael Bailey...
MOBIHOC
2000
ACM
15 years 8 months ago
Utility-based decision-making in wireless sensor networks
— We consider challenges associated with application domains in which a large number of distributed, networked sensors must perform a sensing task repeatedly over time. We addres...
John W. Byers, Gabriel Nasser
TMC
2010
139views more  TMC 2010»
15 years 2 months ago
Optimize Storage Placement in Sensor Networks
—Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. Storage nodes are introdu...
Bo Sheng, Qun Li, Weizhen Mao