THE 15TH INTERNATIONAL COMPUTER SCIENCE SYMPOSIUM IN RUSSIA

Россия, Екатеринбург

30 июня3 июля 2020

Форма участия: Очная

Срок подачи заявок: 10.01.2020

Индексирование сборника: Springer

Организаторы: Institute of Natural Sciences and Mathematics of  Ural Federal University; European Association for Theoretical Computer Science

emal: [email protected]

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The 15th International Computer Science Symposium in Russia (CSR 2020) will take place at the Ural Federal University, Ekaterinburg, Russia on June 29 – July 3, 2020  under the auspices of the European Association for Theoretical Computer Science (EATCS). The conference will be hosted by the Institute of Natural Sciences and Mathematics of  Ural Federal University.

Authors are invited to submit papers presenting original and unpublished research. The proceedings will be published in the Springer-Verlag Lecture Notes in Computer Science Series (LNCS). Simultaneous submission to journals or other conferences with published proceedings is not allowed.

Submitted papers should not exceed 12 pages and should follow the LNCS-style LaTeX2e. All proofs omitted due to space constraints should be given in an appendix or made accessible through a reliable link to a freely available electronic preprint.  Papers should be submitted electronically in PDF through the EasyChair system.

TOPICS include, but are not limited to:

  • algorithms and data structures

  • computational complexity, including hardness of approximation and parameterized complexity

  • randomness in computing, approximation algorithms, fixed-parameter algorithms

  • combinatorial optimization, constraint satisfaction, operations research

  • computational geometry

  • string algorithms

  • formal languages and automata, including applications to computational linguistics

  • codes and cryptography

  • combinatorics in computer science

  • computational biology

  • applications of logic to computer science, proof complexity

  • database theory

  • distributed computing

  • fundamentals of machine learning, including learning theory, grammatical inference and neural computing

  • computational social choice

  • quantum computing and quantum cryptography

  • theoretical aspects of big data

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