Data mining has been an area of increasing interests during recent years. The association rule discovery problem in particular has been widely studied. However, there are still so...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
The problem of finding locally dense components of a graph is an important primitive in data analysis, with wide-ranging applications from community mining to spam detection and ...
This paper deals with the problem of structuralizing education and training videos for high-level semantics extraction and nonlinear media presentation in e-learning applications....
We propose a new boosting algorithm for sequence classification, in particular one that enables early classification of multiple classes. In many practical problems, we would like...