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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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In classification, semi-supervised learning occurs when a large amount of unlabeled data is available with only a small number of labeled data. In this talk, I will discuss how to combine unlabeled and labeled data to enhance the generalization accuracy of classification. A large margin technique will be presented, which utilizes grouping information from unlabeled data, together with the concept of margins, in a form of regularization controlling the interplay between labeled and unlabeled data. Computational aspects will be discussed through difference convex programming, in addition to a tuning method that involves both labeled and unlabeled data, for tuning in regularization. Finally, numerical examples will be provided.
This work is joint with Junhui Wang.
