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» Performance modeling of component assemblies
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JMLR
2010
163views more  JMLR 2010»
14 years 4 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
CDC
2010
IEEE
139views Control Systems» more  CDC 2010»
14 years 4 months ago
Communication, convergence, and stochastic stability in self-assembly
Existing work on programmable self assembly has focused on deterministic performance guarantees--stability of desirable states. In particular, for any acyclic target graph a binary...
Michael J. Fox, Jeff S. Shamma
ICSE
2011
IEEE-ACM
14 years 1 months ago
Predictable dynamic deployment of components in embedded systems
—Dynamic reconfiguration – the ability to hot swap a component, or to introduce a new component into the system – is essential to supporting evolutionary change in long-live ...
Ana Petricic
SEKE
2004
Springer
15 years 3 months ago
Grammatically Interpreting Feature Compositions
Feature modeling is a popular domain analysis method for describing the commonality and variability among the domain products. The current formalisms of feature modelling do not ha...
Wei Zhao, Barrett R. Bryant, Fei Cao, Rajeev R. Ra...
AAAI
2004
14 years 11 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...