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» Temporal Data Classification Using Linear Classifiers
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142
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ACCV
2010
Springer
14 years 10 months ago
Learning Rare Behaviours
Abstract. We present a novel approach to detect and classify rare behaviours which are visually subtle and occur sparsely in the presence of overwhelming typical behaviours. We tre...
Jian Li, Timothy M. Hospedales, Shaogang Gong, Tao...
130
Voted
ISCAPDCS
2004
15 years 5 months ago
Detecting Grid-Abuse Attacks by Source-based Monitoring
While it provides the unprecedented processing power to solve many large scale computational problems, GRID, if abused, has the potential to easily be used to launch (for instance...
Jianjia Wu, Dan Cheng, Wei Zhao
123
Voted
ISBI
2006
IEEE
16 years 4 months ago
Two probabilistic algorithms for MEG/EEG source reconstruction
We have developed two algorithms for source imaging from MEG/EEG data. Contribution to sensor data from a source at a particular voxel is expressed as the product of a known lead ...
Johanna M. Zumer, Hagai Attias, Kensuke Sekihara, ...
130
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ACMMSP
2004
ACM
101views Hardware» more  ACMMSP 2004»
15 years 9 months ago
Metrics and models for reordering transformations
Irregular applications frequently exhibit poor performance on contemporary computer architectures, in large part because of their inefficient use of the memory hierarchy. Runtime ...
Michelle Mills Strout, Paul D. Hovland
151
Voted
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 4 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher