Probability and Computing (Sommersemester 2019)
Lecturer:
Prof. Dr. Tobias Friedrich
(Algorithm Engineering)
,
Dr. Andreas Göbel
(Algorithm Engineering)
Course Website:
https://hpi.de/en/friedrich/teaching/ss19/probcomp.html
General Information
- Weekly Hours: 4
- Credits: 6
- Graded:
yes
- Enrolment Deadline: 26.04.2019
- Teaching Form: Lecture / Exercise
- Enrolment Type: Compulsory Elective Module
- Course Language: English
- Maximum number of participants: 30
Programs, Module Groups & Modules
- 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
Description
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
Requirements
The course requires knowledge of probability theory and basic knowledge of algorithmic design.
Literature
The main textbook is ``Probability and Computing'' by Mitzenmacher and Upfal.
Examination
Students will be given homework bi-weekly. The successful hand in of homework is required for students to participate in the final exam.
Dates
- Mondays: 13:30-15:00 in HS1
- Wednesdays: 11:00-12:30 in HS1
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