Lecture Prof. Daniela Calvetti

On Tuesday 22nd May at 2.30 pm in the Professors Room I Level of the DMA, Prof. Daniela Calvetti, Case Western Reserve University, will hold a seminar entitled:

"Promoting sparsity with Krylov iterative solvers and hierarchical Bayesian models: the L2 magic."

All interested students are invited to participate.

A brief summary follows.

Hierarchical Bayesian models with suitable choices of hyperpriors, combined with Krylov subspace iterative solvers can be very effective at promoting sparsity in the solution of inverse problems while retaining the $\ell_2$ computational efficiency. The use of Krylov iterative solvers makes these methods particular well suited for large scale problems.  In this talk we present some results about the quadratic convergence of these methods for a family of hyperpriors and illustrate their performance with computed examples.

"Analysis and synthesis of adaptive controls for multi-rotor unmanned aerial vehicles" 

Numerical Methods: Talks announcement

Prof. Florian A. Potra, Department of Mathematics and Statistics, University of Maryland Baltimore County

will give two talks in the course “Numerical Methods”,  according to the following schedule:

• May 17th,  2018, 11.00 am - 1.00 pm (First Level Meeting Room - DMA )
• May 18th, 2018, 2.30 pm - 4.30 pm (First Level Meeting Room - DMA)

The talks will be about the "Interior Point Methods". 

Interior point methods have revolutionized the field of mathematical programming over the past three decades. They have been used for proving polynomial complexity for different classes of mathematical programming problems, and they have been implemented in very efficient software packages for solving large scale optimization problems arising in a variety of applications. While the implemented interior point methods may not always have  proven computational complexity, they typically posses superlinear convergence. 

This two talks highlight the most relevant results in the history  of  interior point methods with emphasis on polynomial complexity and superlinear convergence. It also presents some applications in simulation of multibody dynamics and bioinformatics.