Online Coregularization for Multiview Semisupervised Learning
Figure 2
Four choices of to update multiple dual coefficient vectors. The horizontal thin line on each learning round represents the whole training data sequence, while the thick boxes represent the set of examples whose dual coefficient vectors are used to ascend the dual function on that round. Essentially, different choices of construct different QP problems on each learning round. Obviously, if , the update scheme chooses to solve the largest possible QP on each learning round; and if , the update scheme chooses to solve the smallest possible QP on each learning round.
