65 search results - page 12 / 13 » A bound on the label complexity of agnostic active learning |
IMC
2010
ACM
13 years 2 months ago
2010
ACM
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
UAI
2003
13 years 5 months ago
2003
We formulate a principle for classification with the knowledge of the marginal distribution over the data points (unlabeled data). The principle is cast in terms of Tikhonov styl...
NIPS
2008
13 years 5 months ago
2008
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
BMCBI
2010
13 years 4 months ago
2010
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...