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» Bayesian Evolutionary Optimization Using Helmholtz Machines
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CEC
2009
IEEE
14 years 4 months ago
What is situated evolution?
—In this paper we discuss the notion of situated evolution. Our treatment includes positioning situated evolution on the map of evolutionary processes in terms of time- and space...
Martijn C. Schut, Evert Haasdijk, A. E. Eiben
JMLR
2008
209views more  JMLR 2008»
13 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
BMCBI
2006
118views more  BMCBI 2006»
13 years 10 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
ICML
2007
IEEE
14 years 10 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
PLDI
2003
ACM
14 years 3 months ago
Meta optimization: improving compiler heuristics with machine learning
Compiler writers have crafted many heuristics over the years to approximately solve NP-hard problems efficiently. Finding a heuristic that performs well on a broad range of applic...
Mark Stephenson, Saman P. Amarasinghe, Martin C. M...