731 search results - page 112 / 147 » Taxonomy-superimposed graph mining |
KDD
2010
ACM
13 years 11 months ago
2010
ACM
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
WSDM
2009
ACM
14 years 2 months ago
2009
ACM
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
ISPASS
2009
IEEE
14 years 2 months ago
2009
IEEE
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...