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IJAR
2007
55views more  IJAR 2007»
15 years 6 months ago
Theoretical analysis and practical insights on importance sampling in Bayesian networks
The AIS-BN algorithm [2] is a successful importance sampling-based algorithm for Bayesian networks that relies on two heuristic methods to obtain an initial importance function: -...
Changhe Yuan, Marek J. Druzdzel
154
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SIAMJO
2008
66views more  SIAMJO 2008»
15 years 6 months ago
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating ...
Zizhuo Wang, Song Zheng, Yinyu Ye, Stephen Boyd
ALIFE
2005
15 years 6 months ago
Self-Organizing Hierarchies in Sensor and Communication Networks
We consider a hierarchical multicellular sensing and communication network, embedded in an ageless aerospace vehicle, that is expected to detect and react to multiple impacts and d...
Mikhail Prokopenko, Peter Wang, Philip Valencia, D...
TNN
2008
138views more  TNN 2008»
15 years 6 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany
TSP
2008
167views more  TSP 2008»
15 years 6 months ago
Decentralized Adaptive Filtering Algorithms for Sensor Activation in an Unattended Ground Sensor Network
Abstract--We present decentralized adaptive filtering algorithms for sensor activation control in an unattended ground sensor network (UGSN) comprised of ZigBee-enabled nodes. Node...
Vikram Krishnamurthy, Michael Maskery, Gang George...