Course detail
Information Representation and Machine Learning
FEKT-DKA-IMLAcad. year: 2023/2024
Complexity theory, graph theory, graph equivalence, queuing theory, Petri nets, simulation and modeling, Markov models, advanced evolutionary algorithms.
Language of instruction
English
Number of ECTS credits
4
Mode of study
Not applicable.
Guarantor
Department
Entry knowledge
Not applicable.
Rules for evaluation and completion of the course
final examination
Aims
Objective of this course is to provide information about complexity theeory, graph theory and their comparison, queuing theory, Petri nets, evolution algorithms.
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Goldreich, Oded. "Computational complexity: a conceptual perspective." ACM SIGACT News 39.3 (2008): 35-39. (EN)
Recommended reading
Bürgisser, Peter, Michael Clausen, and Amin Shokrollahi. Algebraic complexity theory. Vol. 315. Springer Science & Business Media, 2013. (EN)
Mitleton-Kelly, Eve. Complex systems and evolutionary perspectives on organisations: the application of complexity theory to organisations. Elsevier Science Ltd, 2003. (EN)
Mitleton-Kelly, Eve. Complex systems and evolutionary perspectives on organisations: the application of complexity theory to organisations. Elsevier Science Ltd, 2003. (EN)
Elearning
eLearning: currently opened course
Classification of course in study plans
Type of course unit
Elearning
eLearning: currently opened course