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» Training a Selection Function for Extraction
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MICCAI
2005
Springer
14 years 8 months ago
Exploiting Temporal Information in Functional Magnetic Resonance Imaging Brain Data
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
CIARP
2005
Springer
14 years 1 months ago
Reward-Punishment Editing for Mixed Data
The KNN rule has been widely used in many pattern recognition problems, but it is sensible to noisy data within the training set, therefore, several sample edition methods have bee...
Raúl Rodríguez-Colín, Jes&uac...
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...
JMLR
2012
11 years 10 months ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
NLPRS
2001
Springer
14 years 4 days ago
Automatically Harvesting Katakana-English Term Pairs from Search Engine Query Logs
This paper describes a method of extracting katakana words and phrases, along with their English counterparts from non-aligned monolingual web search engine query logs. The method...
Eric Brill, Gary Kacmarcik, Chris Brockett