One World Seminar: Mathematical Methods for Arbitrary Data Sources (MADS) /CoursesID:1148

Detailed information

Most recent entry on 2020-06-29 

Organisational Unit

Lehrstuhl für Angewandte Mathematik

Recording type

Vortragsreihe

Via

Free

Language

English

What is Mathematical Methods for Arbitrary Data Sources?

The lecture series will collect talks on mathematical disciplines related to all kind of data, ranging from statistics and machine learning to model-based approaches and inverse problems. Each pair of talks will address a specific direction, e.g., a NoMADS session related to nonlocal approaches or a DeepMADS session related to deep learning.

The series is created in the spirit of the One World Series pioneered by the seminars in probability and PDE.

Using Zoom

For this online seminar we will use zoom as video service. Approximately 15 minutes prior to the beginning of the lecture, a zoom link will be provided on this website and via mailing list.

Mailing list

Please subscribe to our mailing list by filling this form.

Associated Clips

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Gabriel Peyré: Scaling Optimal Transport for High dimensional Learning
2020-04-20
Free
00:46:55
2
Marie-Therese Wolfram: Inverse Optimal Transport
2020-04-20
Free
00:43:03
3
Lorenzo Rosasco: Efficient learning with random projections
2020-05-04
Free
00:47:34
4
Michaël Fanuel: Diversity sampling in kernel method
2020-05-04
Free
00:42:47
5
Lars Ruthotto: Machine Learning meets Optimal Transport: Old solutions for new problems and vice versa
2020-05-18
Free
00:48:42
6
Francis Bach: On the convergence of gradient descent for wide two-layer neural networks
2020-05-18
Free
00:49:31
7
Michael Unser: Representer theorems for machine learning and inverse problems
2020-06-08
Free
00:50:39
8
Vincent Duval: Representing the solutions of total variation regularized problems
2020-06-08
Free
00:45:20
9
Andrea Braides: Continuum limits of interfacial energies on (sparse and) dense graphs
2020-06-15
Free
00:48:06
10
Nicolás García Trillos: Regularity theory and uniform convergence in the large data limit of graph Laplacian eigenvectors on random data clouds
2020-06-15
Free
00:46:09
11
Jana de Wiljes: Sequential learning for decision support under uncertainty
2020-06-29
Free
00:45:13
12
Björn Sprungk: Noise-level robust Monte Carlo methods for Bayesian inference with infomative data
2020-06-29
Free
00:45:56

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