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» Evaluating algorithms that learn from data streams
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EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
15 years 10 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...
130
Voted
CVPR
2007
IEEE
16 years 6 months ago
From Videos to Verbs: Mining Videos for Activities using a Cascade of Dynamical Systems
Clustering video sequences in order to infer and extract activities from a single video stream is an extremely important problem and has significant potential in video indexing, s...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap...
ICASSP
2011
IEEE
14 years 7 months ago
Modified embedding for multi-regime detection in nonstationary streaming data
Many practical data streams are typically composed of several states known as regimes. In this paper, we invoke phase space reconstruction methods from non-linear time series and ...
Evan Kriminger, José Carlos Príncipe...
145
Voted
ICML
2003
IEEE
16 years 4 months ago
Exploration and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Yi Zhang, Wei Xu, James P. Callan
NOSSDAV
2010
Springer
15 years 2 months ago
Reducing data request contentions for improved streaming quality
In P2P assisted multi-channel live streaming systems, it is commonly believed that in unpopular channels, quality degradation is due to the small number of participating peers wit...
Yao Liu, Fei Li, Lei Guo, Songqing Chen