We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this ...
When data instances are inter-related, as are nodes in a social network or hyperlink graph, algorithms for collective classification (CC) can significantly improve accuracy. Recen...
One of the original goals of computer vision was to fully understand a natural scene. This requires solving several sub-problems simultaneously, including object detection, region...
Geremy Heitz, Stephen Gould, Ashutosh Saxena, Daph...