Afonso Bandeira: Katalogdaten im Herbstsemester 2022

NameHerr Prof. Dr. Afonso Bandeira
LehrgebietMathematik
Adresse
Professur für Mathematik
ETH Zürich, HG G 23.1
Rämistrasse 101
8092 Zürich
SWITZERLAND
Telefon+41 44 632 79 54
E-Mailbandeira@math.ethz.ch
DepartementMathematik
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
401-3940-72LStudent Seminar in Mathematics and Data: Differential Privacy Belegung eingeschränkt - Details anzeigen
Number of participants limited to 12.
4 KP2SA. Bandeira, M. T. Boedihardjo
Kurzbeschreibung
Lernziel
401-4944-DRLMathematics of Data Science Belegung eingeschränkt - Details anzeigen
Only for ZGSM (ETH D-MATH and UZH I-MATH) doctoral students. The latter need to register at myStudies and then send an email to info@zgsm.ch with their name, course number and student ID. Please see https://zgsm.math.uzh.ch/index.php?id=forum0
2 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.
Skripthttps://people.math.ethz.ch/~abandeira/BandeiraSingerStrohmer-MDS-draft.pdf
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
complementary.
A. Bandeira and H. Bölcskei
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.
Skripthttps://people.math.ethz.ch/~abandeira/BandeiraSingerStrohmer-MDS-draft.pdf
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
complementary.
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.
Lernziel
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
Lernziel
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, N. Meinshausen, 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:
http://stat.ethz.ch/events/zukost
Lehrsprache ist Englisch oder Deutsch je nach ReferentIn.
401-5660-00LDACO Seminar Information 0 KP1KA. Bandeira, R. Weismantel, R. Zenklusen
KurzbeschreibungResearch colloquium
Lernziel
401-5680-00LFoundations of Data Science Seminar Information 0 KPP. L. Bühlmann, A. Bandeira, H. Bölcskei, S. van de Geer, F. Yang
KurzbeschreibungResearch colloquium
Lernziel