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WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
16 years 4 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
FOCS
1990
IEEE
15 years 10 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
CIKM
2010
Springer
15 years 5 months ago
Multi-view clustering with constraint propagation for learning with an incomplete mapping between views
Multi-view learning algorithms typically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. However, ma...
Eric Eaton, Marie desJardins, Sara Jacob
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
215
Voted
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto