• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
ФКН
Contacts

109028, Moscow,
11, Pokrovsky boulevard

Phone: +7 (495) 531-00-00 *27254

Email: computerscience@hse.ru

 

Administration
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
Article
A randomized coordinate descent method with volume sampling

Rodomanov A., Kropotov D.

SIAM Journal on Optimization. 2020. Vol. 30. No. 3. P. 1878-1904.

Article
ML-assisted versatile approach to Calorimeter R&D

A. Boldyrev, D. Derkach, F. Ratnikov et al.

Journal of Instrumentation. 2020. Vol. 15. P. 1-7.

Article
An accelerated directional derivative method for smooth stochastic convex optimization

Dvurechensky P., Eduard Gorbunov, Gasnikov A.

European Journal of Operational Research. 2021. Vol. 290. No. 2. P. 601-621.

Book chapter
On pattern setups and pattern multistructures

Kuznetsov S., Kaytoue M., Belfodil A.

In bk.: International Journal of General Systems. Iss. 49. 2020. P. 271-285.

Book chapter
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise

Kaledin M., Moulines E., Naumov A. et al.

In bk.: Proceedings of Machine Learning Research. Vol. 125: Proceedings of Thirty Third Conference on Learning Theory. 2020. P. 2144-2203.

Summer school on Machine Learning in High Energy Physics

This is the first announcement of the MLHEP Summer School onMachine Learning for High Energy Physics, to be held atSaint-Petersburg, Russia, just before LHC Physics Conference on  August 27-30, 2015.

The primary goal of this year's MLHEP school will be a focused introduction to modern machine learning techniques that could improve physics performance for variety of HEP problems. School pays attention to student experience, so along with "hands-on" seminars a dedicated data science competition will be organized.
Additionally, the school will include series of talks that show real examples of improvements for particular physics cases due to machine learning techniques.
The school is ideally suited for advanced graduate students and young postdocs.
For further information, including application procedures, pleaserefer to the Summer School website or contact mlhep2015@yandex.ru.