SubjectsSubjects(version: 953)
Course, academic year 2023/2024
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Stochastic Programming and Approximation - NMEK615
Title: Stochastické programování a aproximace
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: both
E-Credits: 2
Hours per week, examination: 0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Note: you can enroll for the course repeatedly
you can enroll for the course in winter and in summer semester
Guarantor: doc. RNDr. Petr Lachout, CSc.
Class: Pravděp. a statistika, ekonometrie a fin. mat.
Classification: Mathematics > Probability and Statistics
Is interchangeable with: NSTP134
Annotation -
Research seminar for PhD students.
Last update: T_KPMS (06.05.2014)
Aim of the course -

The objective is (i) getting a view of new trends and new results in stochastic programming and its applications, (ii) discussing the results of the participants before a qualified auditory,

(iii) preparing presentations for conferences and publications.

Last update: T_KPMS (06.05.2014)
Course completion requirements -


Course finalization


The course is finalized by receiving a credit.

Conditions for receiving a credit are:

  • Active attendances.
  • Presentation of a contribution.

Attempt to receive a credit cannot be repeated.

Last update: Lachout Petr, doc. RNDr., CSc. (14.02.2024)
Literature -

According to the chosen topic.

Last update: T_KPMS (29.04.2015)
Teaching methods -


Last update: T_KPMS (06.05.2014)
Entry requirements -

measure and integration theory, probability theory, functional analysis, optimization theory, convex analysis

Last update: Lachout Petr, doc. RNDr., CSc. (30.05.2018)
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