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JMLR
2010
202views more  JMLR 2010»
15 years 1 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
NGC
2010
Springer
183views Communications» more  NGC 2010»
15 years 1 months ago
Brain-like Computing Based on Distributed Representations and Neurodynamics
A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed re...
Ken Yamane, Masahiko Morita
CDC
2008
IEEE
136views Control Systems» more  CDC 2008»
16 years 1 months ago
Estimation over heterogeneous sensor networks
Abstract— Design trade-offs between estimation performance, processing delay and communication cost for a sensor scheduling problem is discussed. We consider a heterogeneous sens...
Henrik Sandberg, Maben Rabi, Mikael Skoglund, Karl...
165
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ISPASS
2008
IEEE
16 years 1 months ago
Conservative vs. Optimistic Parallelization of Stateful Network Intrusion Detection
This paper presents and experimentally evaluates two parallelization strategies for the popular open-source Snort network intrusion detection system (NIDS). Snort identifies intr...
Derek L. Schuff, Yung Ryn Choe, Vijay S. Pai
VTC
2007
IEEE
16 years 28 days ago
Energy-Optimized Low-Complexity Control of Power and Rate in Clustered CDMA Sensor Networks with Multirate Constraints
—In this paper, we propose a low-complexity scheme for minimizing energy consumption in a clustered multirate CDMA sensor network with multiple receive antennas by jointly contro...
Chun-Hung Liu