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JMLR
2006
125views more  JMLR 2006»
13 years 7 months ago
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
Shai Shalev-Shwartz, Yoram Singer
PRL
2010
158views more  PRL 2010»
13 years 6 months ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
CIKM
2009
Springer
14 years 2 months ago
Feature selection for ranking using boosted trees
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
SIGIR
2009
ACM
14 years 2 months ago
A bayesian learning approach to promoting diversity in ranking for biomedical information retrieval
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
Xiangji Huang, Qinmin Hu
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...