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» Genetic Algorithms for Ambiguous Labelling Problems
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ECCV
2010
Springer
13 years 7 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
WWW
2011
ACM
13 years 2 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
BMCBI
2006
127views more  BMCBI 2006»
13 years 7 months ago
Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks
Background: To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to c...
Sok June Oh, Je-Gun Joung, Jeong Ho Chang, Byoung-...
GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
14 years 2 months ago
Swarming along the evolutionary branches sheds light on genome rearrangement scenarios
A genome rearrangement scenario describes a series of chromosome fusion, fission, and translocation operations that suffice to rewrite one genome into another. Exact algorithmic ...
Nikolay Vyahhi, Adrien Goëffon, Macha Nikolsk...
BMCBI
2005
67views more  BMCBI 2005»
13 years 7 months ago
Selecting additional tag SNPs for tolerating missing data in genotyping
Background: Recent studies have shown that the patterns of linkage disequilibrium observed in human populations have a block-like structure, and a small subset of SNPs (called tag...
Yao-Ting Huang, Kui Zhang, Ting Chen, Kun-Mao Chao