Abstract: Probabilistically constrained problems, in which the random variables are finitely distributed, are nonconvex in general and hard to solve. The p-efficiency concept has b...
Output coding is a general method for solving multiclass problems by reducing them to multiple binary classification problems. Previous research on output coding has employed, alm...
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
We propose a method for finding seeds for the local alignment of two nucleotide sequences. Our method uses randomized algorithms to find approximate seeds. We present a dynamic ...