Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of ...
William W. Cohen, Robert E. Schapire, Yoram Singer
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Abstract. Affine registration has a long and venerable history in computer vision literature, and extensive work have been done for affine registrations in IR2 and IR3 . In this pa...
Yu-Tseh Chi, S. M. Nejhum Shahed, Jeffrey Ho, Ming...
In [1], we presented the algebraic signal processing theory, an axiomatic and general framework for linear signal processing. The basic concept in this theory is the signal model d...