FI:IA062 Randomized Algorithms - Course Information

IA062 Randomized Algorithms and Computations

Extent and Intensity

2/2. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).

Teacher(s)

prof. RNDr. Jozef Gruska, DrSc. (lecturer)
RNDr. Matej Pivoluska, Ph.D. (seminar tutor)
RNDr. Michal Ajdarów (seminar tutor)
Mgr. Luděk Matyska (seminar tutor)

Guaranteed by

prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: prof. RNDr. Jozef Gruska, DrSc.
Supplier department: Department of Computer Science – Faculty of Informatics

Timetable

Wed 10:00–11:50 B410

• Timetable of Seminar Groups:

IA062/01: Thu 21. 2. to Thu 16. 5. Thu 12:00–13:50 B410, M. Pivoluska

Prerequisites

No special requiremnts are neede.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Applied Informatics (programme FI, N-AP)
• Information Technology Security (eng.) (programme FI, N-IN)
• Information Technology Security (programme FI, N-IN)
• Bioinformatics (programme FI, N-AP)
• Information Systems (programme FI, N-IN)
• Parallel and Distributed Systems (programme FI, N-IN)
• Computer Graphics (programme FI, N-IN)
• Computer Networks and Communication (programme FI, N-IN)
• Computer Systems (programme FI, N-IN)
• Embedded Systems (eng.) (programme FI, N-IN)
• Embedded Systems (programme FI, N-IN)
• Service Science, Management and Engineering (eng.) (programme FI, N-AP)
• Service Science, Management and Engineering (programme FI, N-AP)
• Social Informatics (programme FI, B-AP)
• Theoretical Informatics (programme FI, N-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
• Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
• Image Processing (programme FI, N-AP)

Course objectives

The aim: randomized algorithms and methods are becoming one of the key tools for an effective solution of a variety of problems in informatics and its aplications practically in all theoretical and aplication areas. After finishing the lecture student will be able: To manage basic techniques to design randomized algorithms; to understand differences concerning power of deterministic and randomized algorithms; to manage basic tools for analysis of randomized algorithms; to work with tail inequalities; to understand power and use of the probabilistic method; to understand power of random walks; to understand power of randomized proofs; to understand basic principles of randomized cryptographic protocols.

Syllabus

• Randomized algorithms and methods.
• Examples of randomized algorithms.
• Methods of game theory.
• Main types of randomized algorithms.
• Randomized complexity classes.
• Chernoff's bounds.
• Moments and deviations.
• Probabilistic methods.
• Markov chains and random walks.
• Algebraic methods.
• Aplications:
• Linear programming.
• Parallel and distributed algoritms.
• Randomization in cryptography.
• Randomized methods in theory of numbers.

Literature

• GRUSKA, Jozef. Foundations of computing. London: International Thompson Computer Press, 1997, xv, 716 s. ISBN 1-85032-243-0. info
• MOTWANI, Rajeev and Prabhakar RAGHAVAN. Randomized algorithms. Cambridge: Cambridge University Press, 1995, xiv, 476. ISBN 0521474655. info

Teaching methods

lectures

Assessment methods

oral exam

Language of instruction

English

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (Spring 2019, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2019/IA062