Abstract. Processing compressed strings without decompression is often essential when dealing with massive data sets. We consider local subsequence recognition problems on strings ...
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
A very common type of a-priori knowledge in pattern analysis problems is invariance of the input data with respect to transformation groups, e.g. geometric transformations of imag...
Image preprocessing stage (also known as iris segmentation) is the first step of the iris recognition process and determines its accuracy. In this paper, we propose a method for ir...
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...