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ECML
2007
Springer
13 years 11 months ago
Learning from Relevant Tasks Only
We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...
Samuel Kaski, Jaakko Peltonen
ICML
2007
IEEE
14 years 5 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
BMCBI
2010
143views more  BMCBI 2010»
13 years 5 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
IEAAIE
2001
Springer
13 years 9 months ago
Selecting a Relevant Set of Examples to Learn IE-Rules
The growing availability of online text has lead to an increase in the use of automatic knowledge acquisition approaches from textual data, as in Information Extraction (IE). Some ...
Jordi Turmo, Horacio Rodríguez
ICML
1996
IEEE
13 years 9 months ago
Discovering Structure in Multiple Learning Tasks: The TC Algorithm
Recently, there has been an increased interest in "lifelong" machine learning methods, that transfer knowledge across multiple learning tasks. Such methods have repeated...
Sebastian Thrun, Joseph O'Sullivan