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...
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...
—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 ...
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...
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...