In Machine Learning (ML) algorithms, one of the crucial issues is the representation of the data. As the data become heterogeneous and large-scale, single kernel methods become insufficient to classify nonlinear data. The finite combinations of kernels are limited up to a finite choice. In order to overcome this discrepancy, we propose a novel method of ”infinite” kernel combinations for learni...

The characteristic asymptotic fields at the tip of sharp, semi-infinite cracks and notches are first compared with corresponding features present in selected finite bodies (edge cracks and notches). This gives an explicit view of the gradual divergence of the semiinfinite and finite problem solutions as the observation point becomes remote from the tip. Hence, upper bounds for the local plastic...

The goals of this thesis are the development of global optimization algorithms for semiinfinite and generalized semi-infinite programs and the application of these algorithms to kinetic model reduction. The outstanding issue with semi-infinite programming (SIP) was a methodology that could provide a certificate of global optimality on finite termination for SIP with nonconvex functions particip...

in this paper we give conditions for a tuple of commutative bounded linear operators which holds in the property of the hypercyclicity criterion. we characterize topological transitivity and semi-hereiditarily of a dynamical system given  by an n-tuple of operators acting on a separable infinite dimensional banach space .

Finite linear least squares is one of the core problems numerical algebra, with countless applications across science and engineering. Consequently, there a rich ongoing literature on algorithms for solving problems. In this paper, we explore variant in which system's matrix has infinite dimension (i.e., it quasimatrix). We call such semi-infinite regression As show, case arises several applica...