Fractional derivatives are a mathematical tool that receivedmuch attention in the last decades because of their non-local behaviorwhich has been demonstrated to be useful when modeling anomalousdiffusion phenomena appearing, e.g., in imaging or…

# Categoria evento: Seminar on Numerical Analysis

## Structure-preserving dynamical model order reduction of parametric Hamiltonian systems – Cecilia Pagliantini (TU Eindhoven)

In real-time and many-query simulations of parametric differential equations, computational methods need to face high computational costs to provide sufficiently accurate and stable numerical solutions. To address this issue, model order reduction…

## Computation of generalized matrix functions with rational Krylov methods – Igor Simunec (Scuola Normale Superiore)

Venue: Aula Magna, Dipartimento di Matematica. Generalized matrix functions [3] are an extension of the notion of standard matrix functions to rectangular matrices, defined using the singular value decomposition instead of an eigenvalue…

## Conservative iterative solvers in computational fluid dynamics – Philipp Birken (Lund University)

The governing equations in computational fluid dynamics such as the Navier-Stokes- or Euler equations are conservation laws. Finite volume methods are designed to respect this and the theorem of Lax-Wendroff underscores the importance of it. It…

## Geometric means of quasi-Toeplitz matrices – Jie Meng (University of Pisa)

We study means of geometric type of quasi-Toeplitz matrices, that are semi-infinite matricesA = (a_{i,j}) i,j=1,2,… of the form A = T(a) + E, where E represents a compact operator, and T(a) is a semi-infinite Toeplitz matrix associated with the…

## Compatibility, embedding and regularization of non-local random walks on graphs – Davide Bianchi (University of Insubria, Como, Italy)

Several variants of the graph Laplacian have been introduced to model non-local diffusion pro- cesses, which allow a random walker to “jump” to non-neighborhood nodes, most notably the path graph Laplacians and the fractional graph Laplacian, see…

## (Sparse) Linear Algebra at the Extreme Scales – Fabio Durastante (IAC-CNR)

Sparse linear algebra is essential for a wide variety of scientific applications. The availability of highly parallel sparse solvers and preconditioners lies at the core of pretty much all multi-physics and multi-scale simulations. Technology is…

## A tensor method for semi-supervised learning – Francesco Tudisco (GSSI)

Semi-supervised learning is the problem of finding clusters in a graph or a point-clould dataset where we are given “few” initial input labels. Label Spreading (LS) is a standard technique for this problem, which can be interpreted as a diffusion…

## Efficient iterative methods for the solution of Generalized Lyapunov Equations: Block vs. point Krylov projections, and other controversial decisions – Daniel Szyld (Temple University)

There has been a flurry of activity in recent years in the area of solution of matrix equations. In par- ticular, a good understanding has been reached on how to approach the solution of large scale Lya- punov equations. An effective way to solve…

## Flanders’ theorem for many matrices under commutativity assumptions – Fernando De Terán (Universidad Carlos III de Madrid)

Given two matrices $A \in C^{m \times n}$ and $B \in C^{n \times m}$ , it is known [1] that theJordan canonical form of AB and BA can only differ in the sizes of theJordan blocks associated with the eigenvalue zero, and the difference in thesize of…