Andrea Ulliana (Universität Zürich)
Title T.B.A.
13:30 • UZH Irchel, Winterthurerstrasse 190, Zürich, Building Y27, Room H 28
Dr. Olivier de Gaay Fortman (University of Utrecht)
Title T.B.A.
13:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43
Alina Ostafe (UNSW)
Abstract:
Title: TBA Abstract: TBA Alte Universität - Seminarraum -201
14:15 • Universität Basel
Antoine Pinardin (Universität Basel)
Finite simple subgroups of the real Cremona group of rank three abstract
Abstract:
Very little is known about the classification of finite subgroups of Cremona in dimension three. It is natural to start with the case of simple groups, and this step was achieved by Prokhorov in 2009 over the field of complex numbers. In the work I will present, we show that the only non-cyclic finite simple subgroups of the real Cremona group of rank three are A5 and A6. This is a joint project with I. Cheltsov and Y. Prokhorov.
15:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43
Prof. Dr. Daniel Kressner (EPFL Lausanne)
Randomized linear algebra in scientific computing abstract
Abstract:
Randomized algorithms are becoming increasingly popular in matrix computations. In fact, randomization is on the verge of replacing existing deterministic techniques for several large-scale linear algebra tasks in scientific computing. The poster child of these developments, randomized SVD, is now one of the state-of-the-art approaches for performing low-rank approximation. In this talk, we will go beyond the randomized SVD and illustrate the great potential of randomization to not only speed up existing algorithms, but to also yield novel and often simple algorithms for solving notoriously difficult problems. Examples covered in this talk include reduced order modeling, acceleration of scientific simulations, joint diagonalization, and large null space computation. A common theme of these developments is that randomization helps to transform linear algebra results that only hold generically into robust and reliable numerical algorithms.
16:30 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 19.2
Dr. Francesco Pedrotti (ETH Zürich, Switzerland)
Cutoff for the proximal sampler via transport inequalities abstract
Abstract:
The cutoff phenomenon is a sharp transition in the convergence of high-dimensional Markov chains to equilibrium: the total variation distance remains close to 1 for a long time and then rapidly decreases to almost 0 over a much shorter time window.It was initially discovered in the context of card shuffling by Diaconis and Shahshahani, and since then observed in a variety of different models. In spite of its ubiquity, it is still largely unexplained, and most proofs are model-specific.In this talk, we discuss a high-level approach to establishing cutoff based on transport inequalities, and we illustrate it on a popular algorithm known as the proximal sampler, when the target measure on R^d is log-concave.Based on joint work with Justin Salez.
17:15 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room G 43