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...
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...
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...
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...
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...