Date/Time : 12 Dec 2023 15:00
Venue : S17 #04-06 (SR1)
Speaker : Maxim Raginsky, University of Illinois at Urbana-Champaign

The majorizing measure theorem of Fernique and Talagrand is a fundamental result in the theory of random processes. It relates the boundedness of random processes indexed by elements of a metric space to complexity measures arising from certain multiscale combinatorial structures, such as packing and covering trees. In this talk, based on joint work with Yifeng Chu, I will build on the ideas first outlined in a little-noticed preprint of Andreas Maurer to present an information-theoretic perspective on the majorizing measure theorem, according to which the boundedness of random processes is phrased in terms of the existence of efficient variable-length codes for the elements of the indexing metric space. I will close by discussing the relevance of these results to the analysis of statistical performance of machine learning algorithms through the lens of data compression and the Minimum Description Length principle.

Add to calendar :

Date/Time : 31 Aug 2023 15:00
Venue : S17 #04-06 (SR1)
Speaker : Ofer Zeitouni, Weizmann Institute and NYU Courant

The extreme value theory for Gaussian logarithmically correlated fields has emerged in the last decade as a powerful tool in the analysis of interface models, quantum gravity, random matrices and in a myriad of other applications.

The two dimensional Gaussian free field (and its discrete analogue) is an important motivating example of such a field. In this lecture, I will describe the relation and differences between the extreme value theory for i.i.d. variables and that for Gaussian logarithmically correlated fields, and discuss a sample of non-Gaussian examples.

Add to calendar :

Date/Time : 28 Aug 2023 14:00
Venue : S17 #04-06 (SR1)
Speaker : Gao Ziyang, Leibniz Universitat Hannover

It is a fundamental question in mathematics to find rational solutions to a given system of polynomials, and in modern language this question translates into finding rational points in algebraic varieties. This question is already very deep for algebraic curves defined over Q. An intrinsic natural number associated with the curve, called its genus, plays an important role in studying the rational points on the curve. In 1983, Faltings proved the famous Mordell Conjecture (proposed in 1922), which asserts that any curve of genus at least 2 has only finitely many rational points. Thus the problem for curves of genus at least 2 can be divided into several grades: finiteness, bound, uniform bound, effectiveness. An answer to each grade requires a better understanding of the distribution of the rational points.

In my talk, I will explain the historical and recent developments of this problem according to the different grades. Another important topic on studying points on curves is the torsion packets. This topic goes beyond rational points. I will also discuss briefly about it in my talk.

Add to calendar :

Date/Time : 24 Aug 2023 14:00
Venue : S17 #04-06 (SR1) (Colloquium (joint with IMS))
Speaker : Yujiro Kawamata, University of Tokyo

We will describe infinitesimal deformations of complex manifolds to the direction of something having possibly non-commutative structure sheaves by using Hochschild cohomology. We will also describe global non-commutative deformations of some surfaces.

Add to calendar :

Date/Time : 08 Aug 2023 15:00
Venue : S17 #05-12 (SR4)
Speaker : Barbara Wohlmuth, Technical University of Munich

In this talk, we discuss several aspects of time‐fractional differential operators. The non‐local nature of the operator is challenging from a theoretical and algorithmic point of view but allows us to account for memory effects in the mathematical model. We consider a wide class of time‐fractional PDE models, including gradient flow, viscoelasticity, random field generators, and polymeric fluids. Of special interest is the equivalence of the time fractional gradient flow model with an integer order system in a higher dimension. Exploiting this equivalence allows us to construct efficient algorithms for time fractional PDEs. Replacing the kernel by a finite sum of exponentials transforms the non‐local PDE into an integer‐order system for the modes. To balance the discretization error in time and space with the kernel approximation error, the number of modes has to grow logarithmically. However, we observe numerically that the number of modes is very moderate if the finite sum of exponentials is based on a rational approximation of the kernel function. In this talk, we present theoretical existence results, algorithmic aspects and show several applications in which fractional operators play an important role. Numerical examples illustrate the large flexibility of the proposed techniques.

Joint work with Marvin Fritz (RICAM, Austria), Brendan Keith (Brown University, USA), Ustim Khristenko (Safran, France) and Endre Süli (University of Oxford, UK).

Add to calendar :

Date/Time : 27 Jul 2023 15:00
Venue : S17-04-06 (SR 1)
Speaker : Weinan E, AISI and Peking University

For many years, the lack of good algorithms has severely limited our ability to conduct scientific research. At its heart, the difficulty comes from the notorious “curse of dimensionality” problem. Deep learning is exactly the kind of tool needed to address this problem. In the last few years, we have seen a tremendous amount of scientific progress made as a result of the AI revolution, both in our ability to make use of the fundamental principles of physics and in our ability to make use of experimental data.

In this talk, I will analyze the origin of the AI for Science revolution, review some of the major progresses made so far, and discuss how it will impact the way we do scientific research.

Add to calendar :

Date/Time : 17 May 2023 14:00
Venue : S17 #04-06 (SR1)
Speaker : Susanne Brenner, Lousiana State University

Elliptic optimal control problems are infinite dimensional least-squares data fitting problems where the models are defined by second order elliptic boundary value problems. In the presence of pointwise constraints on the state variable, the traditional approach becomes more challenging due to the reduced regularity of the adjoint state. In this talk I will explain how to adopt finite element methods originally designed for fourth order elliptic boundary value problems to this class of optimal control problems and present a unified framework for their analysis.

Add to calendar :

Date/Time : 15 May 2023 16:00
Venue : S17 #04-06 (SR1)
Speaker : Jeong Han Kim, Korea Institute for Advanced Study

Majority dynamics on a graph G is a deterministic process such that every vertex updates its +/- 1-assignment according to the majority assignment on its neighbor simultaneously at each step. Benjamini, Chan, O’Donnell, Tamuz and Tan conjectured that, in the Erdos-Renyi random graph G(n,p), the random initial +/- 1-assignment converges to a 99%-agreement with high probability whenever p = \omega(1/n). This conjecture was first confirmed for p > \lambda n^{-1/2} for a large constant \lambda by Fountoulakis, Kang and Makai. Although this result has been reproved recently by Tran and Vu and by Berkowitz and Devlin, it was unknown whether the conjecture holds for p < \lambda n^{-1/2} . We break this \Omega(n^{-1/2})-barrier by proving the conjecture for sparser random graphs G(n,p), where \lambda’ n^{-3/5} \log n < p < \lambda n^{-1/2} with a large constant \lambda’ > 0.

(Joint work with D. Chakraborti, J. Lee, and T. Tran)

Add to calendar :

Date/Time : 12 May 2023 14:00
Venue : S17 #04-06 (SR1)
Speaker : Chan Hon Fu Raymond, City University of Hong Kong

With the advances in sensor technology, data has become ubiquitous. To make sense of data we have to solve higher and higher dimensional problems that may seem intractable. However, many high-dimensional problems have solutions that live in low-dimensional spaces. Sparsity is a way to exploit the low-dimensional structure of the solutions to obtain feasible solutions for high-dimensional problems. In this talk, we will see how sparsity can be applied to facilitate the solutions of imaging problems, including magnetic resonance imaging, single-molecule localisation microscopy, and ground-based astronomy.

Add to calendar :