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» Learning to Rank with Supplementary Data
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WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
14 years 1 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
BMCBI
2006
134views more  BMCBI 2006»
13 years 8 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...
EDM
2010
128views Data Mining» more  EDM 2010»
13 years 9 months ago
Using Educational Data Mining Methods to Study the Impact of Virtual Classroom in E-Learning
In the past few years, Iranian universities have embarked to use e-learning tools and technologies to extend and improve their educational services. After a few years of conducting...
Mohammad Hassan Falakmasir, Jafar Habibi
WWW
2009
ACM
14 years 8 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang
WSDM
2010
ACM
211views Data Mining» more  WSDM 2010»
14 years 23 days ago
IntervalRank - Isotonic Regression with Listwise and Pairwise Constraints
Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
Taesup Moon, Alex Smola, Yi Chang, Zhaohui Zheng