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ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
14 years 2 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard
TMI
2010
206views more  TMI 2010»
13 years 2 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
14 years 7 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
14 years 1 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
ICASSP
2008
IEEE
14 years 1 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu