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ICML
2005
IEEE
14 years 8 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
IJCAI
2007
13 years 9 months ago
Change of Representation for Statistical Relational Learning
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
PAKDD
2005
ACM
96views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Kernels over Relational Algebra Structures
Abstract. In this paper we present a novel and general framework based on concepts of relational algebra for kernel-based learning over relational schema. We exploit the notion of ...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
WEBI
2005
Springer
14 years 1 months ago
Measuring the Relative Performance of Schema Matchers
Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...
Shlomo Berkovsky, Yaniv Eytani, Avigdor Gal
WSDM
2010
ACM
160views Data Mining» more  WSDM 2010»
14 years 5 months ago
Learning Concept Importance Using a Weighted Dependence Model
Modeling query concepts through term dependencies has been shown to have a significant positive effect on retrieval performance, especially for tasks such as web search, where rel...
Michael Bendersky, Donald Metzler, W. Bruce Croft