In recent years, privacy preserving data mining has become an important problem because of the large amount of personal data which is tracked by many business applications. In many...
Statistical topic models such as the Latent Dirichlet Allocation (LDA) have emerged as an attractive framework to model, visualize and summarize large document collections in a co...
Ramesh Nallapati, Amr Ahmed, William W. Cohen, Eri...
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
Recent years have witnessed increased interest in computing strongly correlated pairs in very large databases. Most previous studies have been focused on static data sets. However...