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JMLR
2012
11 years 9 months ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 7 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
WABI
2009
Springer
117views Bioinformatics» more  WABI 2009»
14 years 1 months ago
A Simulation Study Comparing Supertree and Combined Analysis Methods Using SMIDGen
Background: Supertree methods comprise one approach to reconstructing large molecular phylogenies given multi-marker datasets: trees are estimated on each marker and then combined...
M. Shel Swenson, François Barbançon,...
BMCBI
2006
134views more  BMCBI 2006»
13 years 7 months ago
Application of machine learning in SNP discovery
Background: Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given ...
Lakshmi K. Matukumalli, John J. Grefenstette, Davi...
KDD
2001
ACM
118views Data Mining» more  KDD 2001»
14 years 7 months ago
Infominer: mining surprising periodic patterns
In this paper, we focus on mining surprising periodic patterns in a sequence of events. In many applications, e.g., computational biology, an infrequent pattern is still considere...
Jiong Yang, Wei Wang 0010, Philip S. Yu