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» Strong Separation of Learning Classes
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BMCBI
2006
127views more  BMCBI 2006»
15 years 5 months ago
Automatic discovery of cross-family sequence features associated with protein function
Background: Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomic...
Markus Brameier, Josien Haan, Andrea Krings, Rober...
SIAMIS
2010
378views more  SIAMIS 2010»
15 years 16 days ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
CVPR
2007
IEEE
16 years 7 months ago
Parameter Sensitive Detectors
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
140
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GECCO
2009
Springer
16 years 11 days ago
On the performance effects of unbiased module encapsulation
A recent theoretical investigation of modular representations shows that certain modularizations can introduce a distance bias into a landscape. This was a static analysis, and em...
R. Paul Wiegand, Gautham Anil, Ivan I. Garibay, Oz...
149
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FUZZIEEE
2007
IEEE
16 years 1 days ago
Mining and Predicting CpG islands
— A DNA sequence can be described as a string composed of four symbols: A, T, C and G. Each symbol represents a chemically distinct nucleotide molecule. Combinations of two nucle...
Christopher Previti, Oscar Harari, Coral del Val