Over the years, many Linear Discriminant Analysis (LDA) algorithms have been proposed for the study of high dimensional data in a large variety of problems. An intrinsic limitatio...
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Multiple memory module architecture offers higher performance by providing potentially doubled memory bandwidth. Two key problems in gaining high performance in this kind of archi...
While providing a uniform syntax and a semistructured data model, XML does not express semantics but only structure such as nesting information. In this paper, we consider the prob...