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SIGIR
2006
ACM
16 years 27 days ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
AAAI
2006
15 years 8 months ago
Computing Slater Rankings Using Similarities among Candidates
Voting (or rank aggregation) is a general method for aggregating the preferences of multiple agents. One important voting rule is the Slater rule. It selects a ranking of the alte...
Vincent Conitzer
BMCBI
2007
179views more  BMCBI 2007»
15 years 7 months ago
Gene selection with multiple ordering criteria
Background: A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two co...
James J. Chen, Chen-An Tsai, ShengLi Tzeng, Chun-H...
BMCBI
2004
112views more  BMCBI 2004»
15 years 6 months ago
A double classification tree search algorithm for index SNP selection
Background: In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, ...
Peisen Zhang, Huitao Sheng, Ryuhei Uehara
CORR
2002
Springer
142views Education» more  CORR 2002»
15 years 6 months ago
Learning Algorithms for Keyphrase Extraction
Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases ...
Peter D. Turney