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ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
14 years 3 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
VIS
2007
IEEE
149views Visualization» more  VIS 2007»
14 years 10 months ago
Time Dependent Processing in a Parallel Pipeline Architecture
Pipeline architectures provide a versatile and efficient mechanism for constructing visualizations, and they have been implemented in numerous libraries and applications over the p...
John Biddiscombe, Berk Geveci, Ken Martin, Kenn...
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
14 years 2 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
ISWC
2006
IEEE
14 years 2 months ago
Discovering Characteristic Actions from On-Body Sensor Data
We present an approach to activity discovery, the unsupervised identification and modeling of human actions embedded in a larger sensor stream. Activity discovery can be seen as ...
David Minnen, Thad Starner, Irfan A. Essa, Charles...
CLEF
2006
Springer
14 years 17 days ago
CLEF 2006: Ad Hoc Track Overview
We describe the objectives and organization of the CLEF 2006 ad hoc track and discuss the main characteristics of the tasks offered to test monolingual, bilingual, and multilingual...
Giorgio Maria Di Nunzio, Nicola Ferro, Thomas Mand...