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APBC
2003
128views Bioinformatics» more  APBC 2003»
15 years 8 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
IJCAI
1997
15 years 8 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
170
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PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 11 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
PVLDB
2010
103views more  PVLDB 2010»
15 years 5 months ago
Fast Optimal Twig Joins
In XML search systems twig queries specify predicates on node values and on the structural relationships between nodes, and a key operation is to join individual query node matche...
Nils Grimsmo, Truls Amundsen Bjørklund, Mag...
BMCBI
2010
229views more  BMCBI 2010»
15 years 6 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck