Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
We present new deterministic algorithms for several cases of the maximum rank matrix completion problem (for short matrix completion), i.e. the problem of assigning values to the ...
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
A computationally efficient algorithm is proposed to remove noise impulses from speech and audio signals while retaining its features and tonal quality. The proposed method is bas...