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» Scalable inference in latent variable models
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ICC
2009
IEEE
133views Communications» more  ICC 2009»
14 years 4 months ago
Reducing Average Power in Wireless Sensor Networks through Data Rate Adaptation
—The use of variable data rate can reduce network latency and average power consumption, and automatic rate selection is critical for improving scalability and minimizing network...
Steven Lanzisera, Ankur Mehta, Kristofer S. J. Pis...
IDA
2009
Springer
13 years 7 months ago
Estimating Hidden Influences in Metabolic and Gene Regulatory Networks
We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
Florian Blöchl, Fabian J. Theis
CSDA
2007
169views more  CSDA 2007»
13 years 9 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu
IPPS
2006
IEEE
14 years 3 months ago
Parallelization of module network structure learning and performance tuning on SMP
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...
Hongshan Jiang, Chunrong Lai, Wenguang Chen, Yuron...
KBSE
2010
IEEE
13 years 8 months ago
Solving string constraints lazily
Decision procedures have long been a fixture in program analysis, and reasoning about string constraints is a key element in many program analyses and testing frameworks. Recent ...
Pieter Hooimeijer, Westley Weimer