Veranstaltungen
- Mittwoch, 24.04.2024, 14:15 Uhr (WIAS-ESH)
- Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Prof. Dr. Ruming Zhang, Technische Universität Berlin:
Direct and inverse problems in periodic waveguides
mehr ... Veranstaltungsort
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstrakt
Waveguides play important roles in many application areas, for example, in communications. An essential topic in the development of modern techniques is based on the deep understanding of the behaviours of the waves propagating in the waveguides. Then, numerical methods are proposed to simulate the physical processes and mathematical methods are developed to solve the related inverse problems. In this talk, I will first focus on the direct problem, that is study the timeharmonic wave propagating in the periodic waveguide both analytically and numerically. The problem is modeled by the Helmholtz equation in a periodic strip. Afterwards, I will also introduce one example of the solution to an inverse problem.
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Oberseminar “Nichtlineare Partielle Differentialgleichungen” (Langenbach Seminar)
Veranstalter
Humboldt-Universität zu Berlin
WIAS Berlin
- Mittwoch, 24.04.2024, 11:30 Uhr (WIAS-405-406)
- Seminar Interacting Random Systems
Julia Hörmann, WIAS Berlin:
High-dimensional random tessellations, deep neural networks and image classification in a security relevant setting
mehr ... Veranstaltungsort
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406
Abstrakt
Random tessellations as hyperplane and Voronoi tessellations are probabilistic models studied in stochastic geometry. In the talk a line of research concerning asymptotic properties of random tessellations for growing dimension of the Euclidean space is presented. Random tessellations have applications in data science and multivariate statistics since each classification problem corresponds to the search for a tessellation. Here, in particular deep neural networks are a recent controversial approach with great successes in machine learning challenges on the one hand but the lack of mathematical understanding and robustness on the other hand. For illustration we present the results of a feasibility study concerning the application of deep neural networks in a security relevant setting. Improving the mathematical understanding of deep neural networks is thus a topic of high interest. The talk will be concluded with some open mathematical questions.
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Seminar Interacting Random Systems (Hybrid Event)
Veranstalter
WIAS Berlin
- Mittwoch, 24.04.2024, 11:30 Uhr (WIAS-405-406)
- Seminar Interacting Random Systems
Julia Hörmann, WIAS Berlin:
tba
mehr ... Veranstaltungsort
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406
Weitere Informationen
Seminar Interacting Random Systems (Hybrid Event)
Veranstalter
WIAS Berlin
- Dienstag, 23.04.2024, 15:00 Uhr (WIAS-405-406)
- Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Priv.-Doz. Dr. John Schoenmakers, WIAS Berlin:
Optimal stopping with randomly arriving opportunities to stop
mehr ... Veranstaltungsort
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406
Weitere Informationen
Hybrid event. Dieser Vortrag findet auch via Zoom statt: https://zoom.us/j/492088715
Veranstalter
WIAS Berlin
- Montag, 22.04.2024, 13:30 Uhr (WIAS-ESH)
- Berlin Oberseminar: Optimization, Control and Inverse Problems
Dr. Johannes Royset, University of Souther California, USA:
Approximations of Rockafellians, Lagrangians, and Dual Functions. The case for solving surrogates instead of actual optimization problems
mehr ... Veranstaltungsort
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstrakt
Optimization problems are notorious for being unstable in the sense that small changes in their parameters can cause large changes in solutions. However, Rockafellian relaxations, Lagrangian relaxations, and dual problems are typically more stable. While focusing on the nonconvex case, we develop sufficient conditions under which approximations of Rockafellian relaxations, Lagrangian relaxations, and dual problems convergence, epigraphically or hypographically, to limiting counterparts, and quantify the rate of convergence. The conditions are milder than those required by approximations of the actual problems confirming the importance of these surrogate problems. We illustrate the results in the context of composite problems, stochastic optimization, and Rockafellians constructed by augmentation.
Weitere Informationen
Berlin Oberseminar: Optimization, Control and Inverse Problems
Veranstalter
WIAS Berlin