We present a Resolution-Invariant Image Representation (RIIR) framework in this paper. The RIIR framework includes the methods of building a set of multi-resolution bases from tra...
In recent years, active learning methods based on experimental design achieve state-of-the-art performance in text classification applications. Although these methods can exploit ...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
An algorithm that remains in use at the core of many partitioning systems is the Kernighan-Lin algorithm and a variant the Fidducia-Matheysses (FM) algorithm. To understand the FM...
Wray L. Buntine, Lixin Su, A. Richard Newton, Andr...
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...