In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Background: Biological processes in cells are carried out by means of protein-protein interactions. Determining whether a pair of proteins interacts by wet-lab experiments is reso...
Thahir P. Mohamed, Jaime G. Carbonell, Madhavi Gan...
We present an algorithm for active learning (adaptive selection of training data) within the context of semi-supervised multi-task classifier design. The semi-supervised multi-ta...