We introduce the Spherical Admixture Model (SAM), a Bayesian topic model for arbitrary 2 normalized data. SAM maintains the same hierarchical structure as Latent Dirichlet Allocat...
Joseph Reisinger, Austin Waters, Bryan Silverthorn...
When related learning tasks are naturally arranged in a hierarchy, an appealing approach for coping with scarcity of instances is that of transfer learning using a hierarchical Ba...
Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne ...
Database selection is an important step when searching over large numbers of distributed text databases. The database selection task relies on statistical summaries of the databas...
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
The IBM Task Modeler supports the rapid creation and analysis of hierarchical task models, thereby providing a valuable and naturally visual tool for information architects. Task ...