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» Approximate data mining in very large relational data
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ICCV
2009
IEEE
14 years 11 months ago
Fast realistic multi-action recognition using mined dense spatio-temporal features
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
Andrew Gilbert, John Illingworth, Richard Bowden
CIB
2002
100views more  CIB 2002»
15 years 1 months ago
Web-log Mining for Quantitative Temporal-Event Prediction
The web log data embed much of web users' browsing behavior. From the web logs, one can discover patterns that predict the users' future requests based on their current b...
Qiang Yang, Hui Wang, Wei Zhang
ECAI
2010
Springer
15 years 2 months ago
Context-Specific Independence in Directed Relational Probabilistic Models and its Influence on the Efficiency of Gibbs Sampling
Abstract. There is currently a large interest in relational probabilistic models. While the concept of context-specific independence (CSI) has been well-studied for models such as ...
Daan Fierens
WSDM
2010
ACM
160views Data Mining» more  WSDM 2010»
15 years 11 months ago
Tagging Human Knowledge
A fundamental premise of tagging systems is that regular users can organize large collections for browsing and other tasks using uncontrolled vocabularies. Until now, that premise...
Paul Heymann, Andreas Paepcke, Hector Garcia-Molin...
IJCNN
2000
IEEE
15 years 6 months ago
The Inefficiency of Batch Training for Large Training Sets
Multilayer perceptrons are often trained using error backpropagation (BP). BP training can be done in either a batch or continuous manner. Claims have frequently been made that bat...
D. Randall Wilson, Tony R. Martinez