Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
The jigsaw method empowers students to build their own knowledge through successive engagement through interactions in original group discussions and in expert group discussions. H...
In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discrimin...
This study focused on the integration of a Web shell for supporting emergent-collaboration activities in six graduate courses (115 students) in the Tel-Aviv University School of E...
Rafi Nachmias, David Mioduser, Avigail Oren, Judit...