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ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
14 years 7 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh
CEC
2007
IEEE
15 years 4 months ago
A co-evolutionary framework for regulatory motif discovery
Abstract— In previous work, we have shown how an evolutionary algorithm with a clustered population can be used to concurrently discover multiple regulatory motifs present within...
Michael A. Lones, Andy M. Tyrrell
NOMS
2006
IEEE
15 years 3 months ago
Predicting Machine Availabilities in Desktop Pools
—This paper describes a study of predicting machine availabilities and user presence in a pool of desktop computers. The study is based on historical traces collected from 32 mac...
Artur Andrzejak, Patrício Domingues, Lu&iac...
CORR
2011
Springer
177views Education» more  CORR 2011»
14 years 4 months ago
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS
Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including...
Feng Niu, Christopher Ré, AnHai Doan, Jude ...
SAC
2008
ACM
14 years 9 months ago
Efficient concept clustering for ontology learning using an event life cycle on the web
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
Sangsoo Sung, Seokkyung Chung, Dennis McLeod