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» New ensemble methods for evolving data streams
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SMI
2003
IEEE
140views Image Analysis» more  SMI 2003»
14 years 1 months ago
Capturing the Shape of a Dynamic World - Fast!
Acquiring on-line the evolving shape of a dynamic scene from a handful of video streams may be considered one of the most challenging, but at the same time also most auspicious ta...
Marcus A. Magnor, Hans-Peter Seidel
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
13 years 10 months ago
Active Learning with Model Selection in Linear Regression
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
RECSYS
2010
ACM
13 years 8 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
MDM
2005
Springer
174views Communications» more  MDM 2005»
14 years 2 months ago
GPAC: generic and progressive processing of mobile queries over mobile data
This paper introduces a new family of Generic and Progressive algorithms (GPAC, for short) for continuous mobile queries over mobile objects. GPAC provides a general skeleton that...
Mohamed F. Mokbel, Walid G. Aref
KDD
2006
ACM
153views Data Mining» more  KDD 2006»
14 years 9 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...