AASS WORKSHOP SVAN 2016 - Angelia Nedich

Описание: AASS WORKSHOP SVAN 2016

Angelia Nedich
Distributed Algorithms for Aggregative Games on Graphs

Página do Evento: http://svan2016.sciencesconf.org/

Download dos Vídeos: http://video.impa.br/index.php?page=a...

Stochastic Variational Analysis deals with mathematical models, methods, and theory for decisions under uncertainty. The subject covers a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The area emerged in response to the need of solving (generalized) equations systems, optimization and variational problems whose parameters are, in part, uncertain. Problems of this type arise in stochastic optimization, stochastic equilibrium problems, uncertainty quantification, statistical estimation problems that turn up in a broad variety of engineering, economics, finance, energy networks, signal processing, ecology and biological problems.

The thematic program SVAN2016 will be an excellent opportunity to integrate researchers and professionals in the field of Stochastic Optimization, Control, and Variational Analysis, to develop the area in qualitative and quantitative terms in Brazil and Latin America, encouraging undergraduate and graduate students to specialize in the areas covered by the program, presenting problems and discussing solutions, and through contacts with leading researchers in the area.

IMPA will offer scholarships to help the venue of students, specially from Brazil and South America.

Along the three months of the program we plan to have one workshop, one basic course, five mini courses, special talks, and a closing conference.

The program will start with a workshop on Analysis and Applications of Stochastic Systems, to be held on the week of March 28th, 2016. This inaugural workshop will showcase Variational Analysis and Computational Mathematics topics in

stochastic networks and games;
energy markets and financial mathematics, and
the optimal control and optimization of systems subject to uncertainty.

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