The course is also offered to the students of the fields other than those the course is directly associated with.
Fields of study the course is directly associated with
there are 19 fields of study the course is directly associated with, display
The aim: randomized algorithms and methods are becoming one of the key
tools for an effective solution of a variety of problems in
and its aplications practically in all theoretical and aplication
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.
Randomized algorithms and methods.
Examples of randomized algorithms.
Methods of game theory.
Main types of randomized algorithms.
Randomized complexity classes.
Moments and deviations.
Markov chains and random walks.
Parallel and distributed algoritms.
Randomization in cryptography.
Randomized methods in theory of numbers.
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
Language of instruction
The course is taught annually.
The course is taught: every week.