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DSP
2007
13 years 9 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
ICPR
2006
IEEE
14 years 3 months ago
Fast Linear Discriminant Analysis Using Binary Bases
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...
Feng Tang, Hai Tao
CASES
2005
ACM
13 years 11 months ago
Optimizing stream programs using linear state space analysis
Digital Signal Processing (DSP) is becoming increasingly widespread in portable devices. Due to harsh constraints on power, latency, and throughput in embedded environments, devel...
Sitij Agrawal, William Thies, Saman P. Amarasinghe
GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 3 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
BMCBI
2007
172views more  BMCBI 2007»
13 years 9 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...