63 search results - page 6 / 13 » Learning Interpretable SVMs for Biological Sequence Classifi... |
CORR
2007
Springer
13 years 6 months ago
2007
Springer
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
ML
2002
ACM
13 years 6 months ago
2002
ACM
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
BMCBI
2006
13 years 6 months ago
2006
Background: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insig...
BMCBI
2007
13 years 6 months ago
2007
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
TSP
2010
13 years 1 months ago
2010
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...