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» Learning to Rank with Supplementary Data
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152
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DOCENG
2006
ACM
15 years 9 months ago
NEWPAR: an automatic feature selection and weighting schema for category ranking
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
Fernando Ruiz-Rico, José Luis Vicedo Gonz&a...
116
Voted
ICML
2005
IEEE
16 years 4 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
171
Voted
DICTA
2003
15 years 5 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
145
Voted
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
15 years 8 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diļ...
Xiao Zhang, Prasenjit Mitra
152
Voted
BMCBI
2010
154views more  BMCBI 2010»
15 years 3 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...