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ICCV
2009
IEEE
15 years 1 months ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...
GECCO
2008
Springer
115views Optimization» more  GECCO 2008»
13 years 9 months ago
A genetic programming approach to business process mining
The aim of process mining is to identify and extract process patterns from data logs to reconstruct an overall process flowchart. As business processes become more and more comple...
Chris J. Turner, Ashutosh Tiwari, Jörn Mehnen
RECOMB
2003
Springer
14 years 8 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
SIGGRAPH
2003
ACM
14 years 1 months ago
TensorTextures
This paper introduces a tensor framework for image-based rendering. In particular, we develop an algorithm called TensorTextures that learns a parsimonious model of the bidirectio...
M. Alex O. Vasilescu, Demetri Terzopoulos
IJIT
2004
13 years 10 months ago
Computing Entropy for Ortholog Detection
Abstract-- Biological sequences from different species are called orthologs if they evolved from a sequence of a common ancestor species and they have the same biological function....
Hsing-Kuo Pao, John Case