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KDD
2004
ACM
160views Data Mining» more  KDD 2004»
14 years 9 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 3 months ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins
COLT
2008
Springer
13 years 10 months ago
Learning from Collective Behavior
Inspired by longstanding lines of research in sociology and related fields, and by more recent largepopulation human subject experiments on the Internet and the Web, we initiate a...
Michael Kearns, Jennifer Wortman
EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 1 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
ICONIP
2007
13 years 10 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor