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Regular version of the site

125319, Moscow,
3 Kochnovsky Proezd (near metro station 'Aeroport'). 

Phone: +7 (495) 772-95-90 *12332

Email: computerscience@hse.ru



Dean Ivan Arzhantsev

First Deputy Dean Tamara Voznesenskaya

Deputy Dean for Research and International Relations Sergei Obiedkov

Deputy Dean for Methodical and Educational Work Ilya Samonenko

Deputy Dean for Development, Finance and Administration Irina Plisetskaya

Jun 12 – Jun 14
submission: 1 May 2019  
Aug 26 – Aug 30
Registration and Poster Submission deadline — May 1, 2019 
Branching rules related to spherical actions on flag varieties
In press

Roman Avdeev, Petukhov A.

Algebras and Representation Theory. 2019.

Minimax theorems for American options without time-consistency

Belomestny D., Kraetschmer V., Hübner T. et al.

Finance and Stochastics. 2019. Vol. 23. P. 209-238.

Separable discrete functions: Recognition and sufficient conditions

Boros E., Cepek O., Gurvich V.

Discrete Mathematics. 2019. Vol. 342. No. 5. P. 1275-1292.

Cherenkov detectors fast simulation using neural networks

Kazeev N., Derkach D., Ratnikov F. et al.

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2019.

Book chapter
Averaging Weights Leads to Wider Optima and Better Generalization

Izmailov P., Garipov T., Подоприхин Д. А. et al.

In bk.: Proceedings of the international conference on Uncertainty in Artificial Intelligence (UAI 2018). 2018. P. 876-885.

Faculty Colloquium: From Start to Goal: How Mobile Robots Plan Their Paths (Methods and Algorithms). Speaker: Konstantin Yakovlev, Federal Research Center «Computer Science and Control» / HSE

Event ended

26 March 2019, 18:10, room 205 (Kochnovskii proezd, 3)

Konstantin Yakovlev

Associate Professor
Federal Research Center «Computer Science and Control» / HSE


From Start to Goal: How Mobile Robots Plan Their Paths (Methods and Algorithms)

The ability to move is the key feature of mobile intelligent agents such as mobile robots. No wonder that the problem of autonomous naviga-tion has been extensively studied in robotics and artificial intelligence. One of the prominent approaches is to decompose the navigation task into a series of subtasks such as localization, mapping, path planning, trajectory following, etc. In this talk, we will focus on one of such tasks, namely, on path planning (aka path finding), and will explore modern methods and algorithms tailored to solve it.



Faculty Colloquium