Novel Robust Kernels for Visual Learning Problems

Robustness, which is the ability of learning algorithms to resist data disturbance and irrelevant data variations, is very critical for most visual learning systems. One usually has to collect a large number of examples in order to train a model that is robust against different kinds of data disturbance or variations. On the other hand, because the distribution of data is often highly nonlinear in the input space, a robust learning solution can...