Stability of Transductive Regression Algorithms
published: Aug. 1, 2008, recorded: July 2008, views: 134
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
This paper uses the notion of algorithmic stability to derive novel generalization bounds for several families of transductive regression algorithms, both by using convexity and closed-form solutions. Our analysis helps compare the stability of these algorithms. It suggests that several existing algorithms might not be stable but prescribes a technique to make them stable. It also reports the results of experiments with local transductive regression demonstrating the benefit of our stability bounds for model selection, in particular for determining the radius of the local neighborhood used by the algorithm.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !