Afonso Bandeira: Katalogdaten im Herbstsemester 2021

NameHerr Prof. Dr. Afonso Bandeira
Professur für Mathematik
ETH Zürich, HG G 23.1
Rämistrasse 101
8092 Zürich
Telefon+41 44 632 79 54
BeziehungOrdentlicher Professor

401-3940-71LStudent Seminar in Mathematics and Data: Stochastic Optimization Belegung eingeschränkt - Details anzeigen
Number of participants limited to 12.
4 KP2SA. Bandeira, G. Chinot, N. Zhivotovskii
401-4944-20LMathematics of Data Science8 KP4GA. Bandeira
KurzbeschreibungMostly self-contained, but fast-paced, introductory masters level course on various theoretical aspects of algorithms that aim to extract information from data.
LernzielIntroduction to various mathematical aspects of Data Science.
InhaltThese topics lie in overlaps of (Applied) Mathematics with: Computer Science, Electrical Engineering, Statistics, and/or Operations Research. Each lecture will feature a couple of Mathematical Open Problem(s) related to Data Science. The main mathematical tools used will be Probability and Linear Algebra, and a basic familiarity with these subjects is required. There will also be some (although knowledge of these tools is not assumed) Graph Theory, Representation Theory, Applied Harmonic Analysis, among others. The topics treated will include Dimension reduction, Manifold learning, Sparse recovery, Random Matrices, Approximation Algorithms, Community detection in graphs, and several others.
Voraussetzungen / BesonderesThe main mathematical tools used will be Probability, Linear Algebra (and real analysis), and a working knowledge of these subjects is required. In addition
to these prerequisites, this class requires a certain degree of mathematical maturity--including abstract thinking and the ability to understand and write proofs.

We encourage students who are interested in mathematical data science to take both this course and ``227-0434-10L Mathematics of Information'' taught by Prof. H. Bölcskei. The two courses are designed to be
A. Bandeira and H. Bölcskei
401-5000-00LZurich Colloquium in Mathematics Information 0 KPR. Abgrall, M. Iacobelli, A. Bandeira, A. Iozzi, S. Mishra, R. Pandharipande, Uni-Dozierende
KurzbeschreibungThe lectures try to give an overview of "what is going on" in important areas of contemporary mathematics, to a wider non-specialised audience of mathematicians.
401-5620-00LResearch Seminar on Statistics Information 0 KP1KP. L. Bühlmann, M. H. Maathuis, N. Meinshausen, S. van de Geer, A. Bandeira, R. Furrer, L. Held, T. Hothorn, D. Kozbur, M. Wolf
KurzbeschreibungResearch colloquium
401-5640-00LZüKoSt: Seminar on Applied Statistics Information 0 KP1KM. Kalisch, F. Balabdaoui, A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, M. H. Maathuis, M. Mächler, L. Meier, M. Robinson, C. Strobl, S. van de Geer
KurzbeschreibungEtwa 5 Vorträge zur angewandten Statistik.
LernzielKennenlernen von statistischen Methoden in ihrer Anwendung in verschiedenen Anwendungsgebieten.
InhaltIn etwa 5 Einzelvorträgen pro Semester werden Methoden der Statistik einzeln oder überblicksartig vorgestellt, oder es werden Probleme und Problemtypen aus einzelnen Anwendungsgebieten besprochen.
Voraussetzungen / BesonderesDies ist keine Vorlesung. Es wird keine Prüfung durchgeführt, und es werden keine Kreditpunkte vergeben.
Nach besonderem Programm:
Lehrsprache ist Englisch oder Deutsch je nach ReferentIn.
401-5660-00LDACO Seminar Information 0 KP1KA. Bandeira
KurzbeschreibungResearch colloquium
401-5680-00LFoundations of Data Science Seminar Information 0 KPP. L. Bühlmann, A. Bandeira, H. Bölcskei, F. Yang
KurzbeschreibungResearch colloquium
401-5900-00LOptimization Seminar Information 0 KPA. Bandeira, R. Weismantel, R. Zenklusen
KurzbeschreibungLectures on current topics in optimization
LernzielExpose graduate students to ongoing research acitivites (including applications) in the domain of otimization.
InhaltThis seminar is a forum for researchers interested in optimization theory and its applications. Speakers are expected to stimulate discussions on theoretical and applied aspects of optimization and related subjects. The focus is on efficient algorithms for continuous and discrete optimization problems, complexity analysis of algorithms and associated decision problems, approximation algorithms, mathematical modeling and solution procedures for real-world optimization problems in science, engineering, industries, public sectors etc.