Training an SVM when many (most) data are unlabeled. This thesis considers an approach based on a continuous differentiable formulation of the problem.
Candidate: Andrea Boddi
Start: January 2016
Image credits: http://inverseprobability.com/ncnm/
Semi supervised learning by continuous optimization methods