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» Evaluating algorithms that learn from data streams
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PKDD
2005
Springer
161views Data Mining» more  PKDD 2005»
15 years 10 months ago
Active Sampling for Knowledge Discovery from Biomedical Data
Abstract. We describe work aimed at cost-constrained knowledge discovery in the biomedical domain. To improve the diagnostic/prognostic models of cancer, new biomarkers are studied...
Sriharsha Veeramachaneni, Francesca Demichelis, Em...
MCS
2010
Springer
15 years 9 months ago
Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC
We have previously described an incremental learning algorithm, Learn++ .NC, for learning from new datasets that may include new concept classes without accessing previously seen d...
Gregory Ditzler, Michael D. Muhlbaier, Robi Polika...
ISVC
2007
Springer
15 years 10 months ago
Learning to Recognize Complex Actions Using Conditional Random Fields
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...
Christopher I. Connolly
ICIP
2008
IEEE
16 years 6 months ago
Cross-domain learning methods for high-level visual concept classification
Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...
CVPR
2007
IEEE
15 years 11 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen