Probability and Computing (Sommersemester 2019)
Dozent:
Prof. Dr. Tobias Friedrich
(Algorithm Engineering)
,
Dr. Andreas Göbel
(Algorithm Engineering)
Website zum Kurs:
https://hpi.de/friedrich/teaching/ss19/probcomp.html
Allgemeine Information
- Semesterwochenstunden: 4
- ECTS: 6
- Benotet:
Ja
- Einschreibefrist: 26.04.2019
- Lehrform: Vorlesung / Übung
- Belegungsart: Wahlpflichtmodul
- Lehrsprache: Englisch
- Maximale Teilnehmerzahl: 30
Studiengänge, Modulgruppen & Module
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- IT-Systems Engineering
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-S Spezialisierung
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-T Techniken und Werkzeuge
- ISAE: Internet, Security & Algorithm Engineering
- HPI-ISAE-K Konzepte und Methoden
- DATA: Data Analytics
- HPI-DATA-T Techniken und Werkzeuge
- DATA: Data Analytics
- HPI-DATA-S Spezialisierung
- SCAL: Scalable Data Systems
- HPI-SCAL-K Konzepte und Methode
- SCAL: Scalable Data Systems
- HPI-SCAL-T echniken und Werkzeuge
- SCAL: Scalable Data Systems
- HPI-SCAL-S Spezialisierung
- DATA: Data Analytics
- HPI-DATA-K Konzepte und Methoden
Beschreibung
This lecture will be held in English and consists of of two parts.
In this lecture we will review important techniques and results that combine probability theory and computation. Topics include:
- Randomised Algorithms
- The probabilistic method
- The Markov chain Monte Carlo method
- Random structures and phase transitions
- Discrete time/continuous space random processes
Voraussetzungen
The course requires knowledge of probability theory and basic knowledge of algorithmic design.
Literatur
The main textbook is ``Probability and Computing'' by Mitzenmacher and Upfal.
Leistungserfassung
Students will be given homework bi-weekly. The successful hand in of homework is required for students to participate in the final exam.
Termine
- Mondays: 13:30-15:00 in HS1
- Wednesdays: 11:00-12:30 in HS1
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