Kurssiesite

Laajuus: 5

Aikataulu: 07.01.2019 - 15.02.2019

Kurssin yhteystiedot (koskee tätä kurssikertaa): 

Professors Visa Koivunen, Sergiy Vorobyov, Esa Ollila (e-mail: firstname.lastname@aalto.fi)

Please contact by email. 

Opetusperiodi (voimassa 01.08.2018-31.07.2020): 

III - IV 2018 – 2019, 2019 – 2020 (spring)

Osaamistavoitteet (voimassa 01.08.2018-31.07.2020): 

Students are able to recognize the problems of processing data of large scale problems that arise in engineering and computer science. Students can describe the basic theory of such problems, concentrating on results that are useful in computation. Students have a thorough understanding of how such problems are thought of and addressed, and some experience in solving them. Students can apply the methods in their own research work. Students know a number of examples of successful application of the techniques for signal processing of large scale data. More detailed and revised learning outcomes are presented at the beginning of the course.

Sisältö (voimassa 01.08.2018-31.07.2020): 

Optimization, subgradient methods, statistical learning.

Toteutus, työmuodot ja arvosteluperusteet (voimassa 01.08.2018-31.07.2020): 

Lectures, exercises, assignments.

Työmäärä toteutustavoittain (voimassa 01.08.2018-31.07.2020): 

Lectures, excercises approximately 50 h, assignments and independent studying approximately 83 h, total 133 h

Attendance in some contact teaching may be compulsory.

Korvaavuudet (voimassa 01.08.2018-31.07.2020): 

ELEC-E5430 Signal Processing for Large Scale Data Analysis L

Kurssin kotisivu (voimassa 01.08.2018-31.07.2020): 

https://mycourses.aalto.fi/course/search.php?search=elec-e5431

Esitiedot (voimassa 01.08.2018-31.07.2020): 

Recommended ELEC-E5422 Convex Optimization I P and ELEC-E5440 Statistical Signal Processing P

Arvosteluasteikko (voimassa 01.08.2018-31.07.2020): 

0...5

Ilmoittautuminen (voimassa 01.08.2018-31.07.2020): 

In WebOodi

Lisätietoja (voimassa 01.08.2018-31.07.2020): 

Language Class 3: English

Opintojakson kuvaus

Ilmoittautuminen ja lisätiedot