Suchergebnis: Lehrveranstaltungen im Herbstsemester 2020

Elektrotechnik und Informationstechnologie Master Information
Master-Studium (Studienreglement 2008)
Fächer der Vertiefung
Insgesamt 42 KP müssen im Masterstudium aus Vertiefungsfächern erreicht werden. Der individuelle Studienplan unterliegt der Zustimmung eines Tutors.
Signal Processing and Machine Learning
Empfohlene Fächer
NummerTitelTypECTSUmfangDozierende
227-0101-00LDiscrete-Time and Statistical Signal Processing Information W6 KP4G
227-0101-00 GDiscrete-Time and Statistical Signal Processing
The lecturers will communicate the exact lesson times of ONLINE courses.
4 Std.
Di14:00-18:00ON LI NE »
H.‑A. Loeliger
227-0116-00LVLSI I: From Architectures to VLSI Circuits and FPGAs Information W6 KP5G
227-0116-00 GVLSI I: From Architectures to VLSI Circuits and FPGAs
Lecture: Tue 8 - 10 h
Execises: Wed 13 - 16 h or Thu 09 - 12 h
The lecturers will communicate the exact lesson times of ONLINE courses.
5 Std.
Di08:00-10:00ON LI NE »
Mi13:15-16:00ETZ D 61.1 »
13:15-16:00ETZ D 61.2 »
13:15-16:00ETZ D 96.1 »
Do09:15-12:00ETZ D 61.1 »
09:15-12:00ETZ D 61.2 »
09:15-12:00ETZ D 96.1 »
F. K. Gürkaynak, L. Benini
227-0155-00LMachine Learning on Microcontrollers Belegung eingeschränkt - Details anzeigen
Registration in this class requires the permission of the instructors. Class size will be limited to 16.
Preference is given to students in the MSc EEIT.
W6 KP3G
227-0155-00 GMachine Learning on Microcontrollers Für Fachstudierende und Hörer/-innen ist eine Spezialbewilligung der Dozierenden notwendig.
Bewilligung der Dozierenden für alle Studierenden notwendig.
All the lectures will be remote by zoom.

For exercises we will include a tutorial to install all the software at home.

The lab will be divided in 3 groups and students need physical assistance and can come in their dedicate time in ETZ K63.
3 Std.
Mo13:15-17:00ETZ K 63 »
M. Magno, L. Benini
227-0225-00LLinear System TheoryW6 KP5G
227-0225-00 GLinear System Theory
The lecturers will communicate the exact lesson times of ONLINE courses.
5 Std.
Mo09:00-12:00ON LI NE »
Mi10:00-12:00ON LI NE »
M. Colombino
227-0417-00LInformation Theory IW6 KP4G
227-0417-00 GInformation Theory I
Classroom teaching with lecture recording.
4 Std.
Mi14:15-18:00ETF C 1 »
A. Lapidoth
227-0421-00LLearning in Deep Artificial and Biological Neuronal NetworksW4 KP3G
227-0421-00 GLearning in Deep Artificial and Biological Neuronal Networks3 Std.
Mi09:15-12:00ML H 44 »
B. Grewe
227-0445-10LMathematical Methods of Signal Processing Information W6 KP4G
227-0445-10 GMathematical Methods of Signal Processing
Lecture start is on Tuesday, 6 October 2020.

Remote lecture on Tusdays 8-10h, per Zoom:
Meeting-ID: 994 133 7347
Kenncode: 530642

Remote exercise on Thursdays 14-16h, per Zoom.
Meeting-ID: 863 7709 0433
Kenncode: 170548

The lecturer will communicate the exact lesson times of ONLINE courses.
4 Std.
Di08:00-10:00ON LI NE »
Do14:00-16:00ON LI NE »
H. G. Feichtinger
227-0477-00LAcoustics IW6 KP4G
227-0477-00 GAcoustics I4 Std.
Mo14:15-18:00ETZ E 7 »
K. Heutschi
263-5210-00LProbabilistic Artificial Intelligence Information Belegung eingeschränkt - Details anzeigen W8 KP3V + 2U + 2A
263-5210-00 VProbabilistic Artificial Intelligence
The lectures will mostly be given in a lecture hall with limited attendance (at most 50% of lecture hall capacity). It will be possible to join remotely via zoom with acccess to slides, whiteboard, and speaker camera. Students can interact, e.g. ask questions, physically as well as digitally. The lectures will be recorded via zoom’s recording functionality.
3 Std.
Fr10:15-12:00ETA F 5 »
13:15-14:00ETA F 5 »
A. Krause
263-5210-00 UProbabilistic Artificial Intelligence2 Std.
Do16:00-18:00ON LI NE »
A. Krause
263-5210-00 AProbabilistic Artificial Intelligence2 Std.A. Krause
401-0647-00LIntroduction to Mathematical Optimization Belegung eingeschränkt - Details anzeigen W5 KP2V + 1U
401-0647-00 VIntroduction to Mathematical Optimization
"Hybrid"
Online except in September/October 2020 for students in the Computational Science and Engineering Bachelor's Programme, where this course is mandatory.
Those students will be invited by the lecturer to the classroom teaching (Tue 16-18 ETH Zentrum campus).
As of November 2020 ONLINE for all students.
The lecturers will communicate the exact lesson times of ONLINE courses.
URL for live streaming: Link
2 Std.
Di16:00-18:00ON LI NE »
D. Adjiashvili
401-0647-00 UIntroduction to Mathematical Optimization
Gruppeneinteilung erfolgt über myStudies.
Wed 12-13 or Wed 16-17

The lecturers will communicate the exact lesson times of ONLINE courses.
1 Std.
Mi12:15-13:00HG D 1.2 »
16:00-17:00ON LI NE »
16:15-17:00HG D 1.2 »
D. Adjiashvili
401-3054-14LProbabilistic Methods in Combinatorics Information W6 KP2V + 1U
401-3054-14 VProbabilistic Methods in Combinatorics2 Std.
Mi10:15-12:00HG E 5 »
B. Sudakov
401-3054-14 UProbabilistic Methods in Combinatorics1 Std.
Mo15:15-16:00HG G 3 »
B. Sudakov
401-3621-00LFundamentals of Mathematical Statistics Information W10 KP4V + 1U
401-3621-00 VFundamentals of Mathematical Statistics
The lecturers will communicate the exact lesson times of ONLINE courses.
URL for live streaming: Link
4 Std.
Di08:00-10:00ON LI NE »
Mi10:00-12:00ON LI NE »
S. van de Geer
401-3621-00 UFundamentals of Mathematical Statistics
The lecturers will communicate the exact lesson times of ONLINE courses.
1 Std.
Di12:00-13:00ON LI NE »
S. van de Geer
401-3901-00LMathematical OptimizationW11 KP4V + 2U
401-3901-00 VMathematical Optimization
The lecturers will communicate the exact lesson times of ONLINE courses.
4 Std.
Mo14:00-16:00ON LI NE »
Do10:00-12:00ON LI NE »
R. Zenklusen
401-3901-00 UMathematical Optimization
Gruppeneinteilung erfolgt über myStudies.
Thu 14-16 or Fri 10-12 or Fr 12-14 or Fri 14-16 (depending on demand)

The lecturers will communicate the exact lesson times of ONLINE courses.
2 Std.
Do14:00-16:00ON LI NE »
Fr10:15-12:00CAB G 51 »
12:15-14:00HG E 1.2 »
14:15-16:00HG G 26.1 »
R. Zenklusen
401-4619-67LAdvanced Topics in Computational StatisticsW4 KP2V
401-4619-00 VAdvanced Topics in Computational Statistics
Findet dieses Semester nicht statt.
2 Std.keine Angaben
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