Ridge regression is a well established method to shrink regression parameters towards zero, thereby securing existence of estimates. The present paper investigates several approac...
Most algorithms used for imaging genetics examine statistical effects of each individual genetic variant, one at a time. We developed a new approach, based on ridge regression, to...
Omid Kohannim, Derrek P. Hibar, Jason L. Stein, Ne...
This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...