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» On learning in agent-centered search
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JMLR
2006
113views more  JMLR 2006»
15 years 6 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
NAACL
2010
15 years 4 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
RECSYS
2010
ACM
15 years 4 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
IEAAIE
2004
Springer
15 years 12 months ago
An Algorithm for Incremental Mode Induction
Learning systems have been devised as a way of overcoming the knowledge acquisition bottleneck in the development of knowledge-based systems. They often cast learning to a search p...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...
PKDD
2004
Springer
155views Data Mining» more  PKDD 2004»
15 years 12 months ago
Ensemble Feature Ranking
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
Kees Jong, Jérémie Mary, Antoine Cor...