We present a hierarchical classification model that allows rare objects to borrow statistical strength from related objects that have many training examples. Unlike many of the e...
Ruslan Salakhutdinov, Antonio Torralba, Josh Tenen...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
: We present an automated detector that can predict a student’s future performance on a transfer post-test, a post-test involving related but different skills than the skills stu...
Ryan Shaun Joazeiro de Baker, Sujith M. Gowda, Alb...
Wikipedia vandalism identification is a very complex issue, which is now mostly solved manually by volunteers. This paper presents the main components of a system built by our grou...
We present a bottom-up approach for automatic cancer cell detection in multispectral microscopic thin Pap smear images. Around 4,000 multispectral texture features are explored fo...