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IDEAS
2008
IEEE
80views Database» more  IDEAS 2008»
14 years 4 months ago
Improved count suffix trees for natural language data
With more and more natural language text stored in databases, handling respective query predicates becomes very important. Optimizing queries with predicates includes (sub)string ...
Guido Sautter, Cristina Abba, Klemens Böhm
ECCV
2010
Springer
13 years 10 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
BMCBI
2008
114views more  BMCBI 2008»
13 years 10 months ago
Visualization of large influenza virus sequence datasets using adaptively aggregated trees with sampling-based subscale represen
Background: With the amount of influenza genome sequence data growing rapidly, researchers need machine assistance in selecting datasets and exploring the data. Enhanced visualiza...
Leonid Zaslavsky, Yiming Bao, Tatiana A. Tatusova
JACM
2006
99views more  JACM 2006»
13 years 10 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
BMCBI
2005
100views more  BMCBI 2005»
13 years 10 months ago
EvDTree: structure-dependent substitution profiles based on decision tree classification of 3D environments
Background: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold ...
Jean-Christophe Gelly, Laurent Chiche, Jér&...