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» Adaptive Learning from Evolving Data Streams
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KDD
2000
ACM
121views Data Mining» more  KDD 2000»
15 years 9 months ago
Mining high-speed data streams
Many organizations today have more than very large databases; they have databases that grow without limit at a rate of several million records per day. Mining these continuous dat...
Pedro Domingos, Geoff Hulten
ECML
2006
Springer
15 years 9 months ago
Automatically Evolving Rule Induction Algorithms
Research in the rule induction algorithm field produced many algorithms in the last 30 years. However, these algorithms are usually obtained from a few basic rule induction algorit...
Gisele L. Pappa, Alex Alves Freitas
DAGM
2009
Springer
15 years 12 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters
ECCV
2008
Springer
16 years 7 months ago
Edge-Preserving Smoothing and Mean-Shift Segmentation of Video Streams
Video streams are ubiquitous in applications such as surveillance, games, and live broadcast. Processing and analyzing these data is challenging because algorithms have to be effic...
Sylvain Paris
ISWC
2006
IEEE
15 years 11 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...