052111 VU Advanced Algorithms (2023W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mi 13.09.2023 09:00 bis Mi 20.09.2023 09:00
- Abmeldung bis Sa 14.10.2023 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Montag
02.10.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
03.10.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
09.10.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
10.10.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
16.10.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
17.10.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
23.10.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
24.10.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
30.10.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
31.10.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
06.11.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
07.11.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
13.11.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
14.11.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
20.11.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
21.11.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
27.11.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
28.11.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
04.12.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
05.12.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
11.12.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
12.12.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
08.01.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
09.01.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
15.01.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
16.01.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
22.01.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
23.01.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Montag
29.01.
11:30 - 13:00
Seminarraum 7, Währinger Straße 29 1.OG
Dienstag
30.01.
15:00 - 16:30
Seminarraum 11, Währinger Straße 29 2.OG
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
A total of 100 regular points (100%) can be reached.In each of the two halves of the semester, there will be
- 1 written exam (90 minutes) for up to 40 regular points,
- 2 homework sheets with several small problems each, one of them needs to be presented in class for up to 10 regular points,
resulting in 2 * (40 + 10) = 100 regular points.Up to 20 bonus points can be reached:
- 5 bonus points if you miss at most 3 classes (-1 for every further missed class)
- up to 5 bonus points for active participation in class and on Moodle
- up to 10 bonus points for solving extra problems on a homework sheetPreliminary dates for the exams:
midterm exam: Monday, November 27, 2023
final exam: Tuesday, January 30, 2024
- 1 written exam (90 minutes) for up to 40 regular points,
- 2 homework sheets with several small problems each, one of them needs to be presented in class for up to 10 regular points,
resulting in 2 * (40 + 10) = 100 regular points.Up to 20 bonus points can be reached:
- 5 bonus points if you miss at most 3 classes (-1 for every further missed class)
- up to 5 bonus points for active participation in class and on Moodle
- up to 10 bonus points for solving extra problems on a homework sheetPreliminary dates for the exams:
midterm exam: Monday, November 27, 2023
final exam: Tuesday, January 30, 2024
Mindestanforderungen und Beurteilungsmaßstab
If P is the sum of regular and bonus points received, your grade will be:1, if P >= 89,
2, if P >= 76,
3, if P >= 63,
4, if P >= 50,
5, otherwise.Presence is mandatory for the first lecture. Otherwise, it is not a requirement, but strongly recommended.
If you fail to show up for an exam, you will receive 0 points for this exam.Homework sheets must be submitted before the deadline to be eligible for presentation in class. You can indicate for each problem on a homework sheet whether you would be willing to present it. The presenter for each problem is chosen by the instructors among all those that are willing to present, with ties broken randomly. There will be enough problems so that each student can present twice if everyone is willing to present all problems. If you fail to submit a homework sheet or are not chosen for presentation because you were unwilling to present many of the subproblems or are chosen to present but don't show up, you will receive 0 points.
2, if P >= 76,
3, if P >= 63,
4, if P >= 50,
5, otherwise.Presence is mandatory for the first lecture. Otherwise, it is not a requirement, but strongly recommended.
If you fail to show up for an exam, you will receive 0 points for this exam.Homework sheets must be submitted before the deadline to be eligible for presentation in class. You can indicate for each problem on a homework sheet whether you would be willing to present it. The presenter for each problem is chosen by the instructors among all those that are willing to present, with ties broken randomly. There will be enough problems so that each student can present twice if everyone is willing to present all problems. If you fail to submit a homework sheet or are not chosen for presentation because you were unwilling to present many of the subproblems or are chosen to present but don't show up, you will receive 0 points.
Prüfungsstoff
- all material presented in class
- contents and discussion of all exercise sheets
- reading material as provided on Moodle
- contents and discussion of all exercise sheets
- reading material as provided on Moodle
Literatur
- Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford. Introduction to Algorithms. MIT Press, 2009/2022 (3rd & 4th edition).
- Kleinberg, Jon; Tardos, Éva. Algorithm Design. Pearson, 2006.
- Erickson, Jeff. Algorithms. Online resource: http://algorithms.wtf/Further literature will be provided via Moodle.
- Kleinberg, Jon; Tardos, Éva. Algorithm Design. Pearson, 2006.
- Erickson, Jeff. Algorithms. Online resource: http://algorithms.wtf/Further literature will be provided via Moodle.
Zuordnung im Vorlesungsverzeichnis
Module: AAL
Letzte Änderung: Di 12.09.2023 17:27
- linear programming
- advanced graph algorithms, e.g. for maximum flow
- advanced analysis techniques
- advanced data structures, e.g. heaps and Bloom filters
- randomized algorithms
- online algorithms and competitive analysis
- data stream algorithmsOn successful completion of this course, you will have an in-depth knowledge and understanding of state-of-the-art algorithmic techniques in various areas.The schedule consists of interactive lectures as well as homework discussions.The course has a strong focus on theoretical understanding and mathematical precision and moves rather fast. It is highly recommended that you have successfully completed courses equivalent to the following:- basics in discrete mathematics and linear algebra, e.g. 051110 VO Mathematical Foundations of Computer Science 1
- basic and intermediate topics in algorithms and data structures, e.g. 051024 VU Algorithms and Data Structures 1 and 052100 VU Algorithms and Data Structures 2
- basics in stochastics (probabilities), e.g. 051130 Introductory StatisticsIf you are unsure whether you meet these prerequirements, please come and speak to us.