Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Learning from positive examples occurs very frequently in natural learning. The PAC learning model of Valiant takes many features of natural learning into account, but in most case...
There is a need to restore color images that suffer from distance-dependent degradation during acquisition. This occurs, for example, when imaging through scattering media. There,...
We present a system that classifies pixels in a document image according to marking type such as machine print, handwriting, and noise. A segmenter module first splits an input ...