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Regular version of the site

Entrance Exam

Date of Entrance Exam:

19 August 2021 in two different sessions in each day, morning 10 am  Moscow time (+3 GMT) and evening 19 pm Moscow time (+3 GMT)

An applicant should choose by email to mcv@hse.ru only one day and time session to pass exam, both exam dates are equal and do not imply priority enrollment.

Pre-exam online consultation  on August 17 19:00 pm. (Link by Alina through mcv@hse.ru) 

Entrance exam paper (sample) (PDF, 214 Kb) 

Entrance exam paper (solutions) (PDF, 562 Kb) 

Entrance exam paper VARIANT 2 (PDF, 234 Kb) 

 Entrance exam VARIANT 2 (SOLUTIONS) (PDF, 373 Kb) 

Entrance exam paper from 23 June 2021 (PDF, 101 Kb) 

Recommended resourses for programming part of the Exam paper (DOCX, 13 Kb) 

Recommended literature for math part of the Exam paper: 

1. Cormen, Leiserson, Rivest, Stein. Introduction to Algorithms.

2. Silvanus P. Thompson. Calculus Made Easy.

 Duration: 120 min
Passing grade: 31 and above
Procedure: 

  • The entrance examination is conducted online using proctoring system and offering written tasks
  • To avoid disadvantaging students who may have to access exam in different time zones and places, two examination sessions will be organized (morning and evening sessions).
  • Each test paper consists of several tasks
  • The final grade is based on combined points of all correctly completed tasks in the test paper
  • The decision on candidates is based on the results of the entrance examination
  • During the exam, applicants are allowed to use all kinds of printed reference materials and prohibited from using any electronic devices.

 

Sort Guaide how to use system (PDF, 1.23 Mb) 

EXAMUS instructions (PDF, 2.85 Mb) 



To support You, HSE held on March 25th an entrance exam preparation webinar

  The questionnaire of «Master in Computer Vision» entrance examination covers follow disciplines:

1.                    Linear algebra

Matrices, linear operators, eigenvalues and vectors, and quadratic forms.

2.                    Mathematical analysis

Limits, derivatives, integrals, series of numbers, functions of one and many variables.

3.                    Combinatorics and theory of probabilities

Permutations and combinations, the inclusion-exclusion principle, discrete and continuous random variables, mathematical expectation and variance, distribution function, conditional probability, joint distribution.

4.                    Discrete Mathematics

Boolean algebra, graphs, Euler and Hamiltonian cycle, set theory, binary relations.

5.                    Algorithms and data structures

Computational complexity, merge sort, count sort, stack, queue, list, vector, binary tree, hash table, recursive algorithms, iterative algorithms, backtracking search.

6.                    Programming in C++

The main constructs of the C++ programming language: branches, loops, functions, arrays, pointer arithmetic, recursion, structures, classes, unions, the C standard library, the STL library.

7.                   Programming in Python

The main constructs of the Python programming language: branches, loops, functions, data collections, classes.