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» Large-Scale Support Vector Learning with Structural Kernels
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RECOMB
2007
Springer
14 years 9 months ago
Support Vector Training of Protein Alignment Models
Abstract. Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features like secondary structure, solvent accessibility...
Chun-Nam John Yu, Thorsten Joachims, Ron Elber, Ja...
AAAI
2006
13 years 10 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...
BMCBI
2007
139views more  BMCBI 2007»
13 years 8 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
BMCBI
2008
145views more  BMCBI 2008»
13 years 8 months ago
Directed acyclic graph kernels for structural RNA analysis
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Kengo Sato, Toutai Mituyama, Kiyoshi Asai, Yasubum...
ICML
2004
IEEE
14 years 9 months ago
A hierarchical method for multi-class support vector machines
We introduce a framework, which we call Divide-by-2 (DB2), for extending support vector machines (SVM) to multi-class problems. DB2 offers an alternative to the standard one-again...
Volkan Vural, Jennifer G. Dy