The Passive Aggressive framework [1] is a principled approach to online linear classification that advocates minimal weight updates i.e., the least required so that the current tr...
Gaussian kernels with flexible variances provide a rich family of Mercer kernels for learning algorithms. We show that the union of the unit balls of reproducing kernel Hilbert s...
The main goal of this paper is to develop a numerical procedure for construction of covariance matrices such that for a given covariance structural model and a discrepancy function...
We obtain exponentially accurate Fourier series for nonperiodic functions on the interval [-1, 1] by extending these functions to periodic functions on a larger domain. The series ...
The traditional SPM approach based on bag-of-features (BoF) must use nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effec...