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Regular version of the site
ФКН
Contacts

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

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

computerscience@hse.ru

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

Article
Linear switched dynamical systems on graphs
In print

Protasov V. Y., Cicone A., Guglielmi N.

Nonlinear Analysis: Hybrid Systems. 2018. Vol. 29. P. 165-186.

Article
Final Results of the OPERA Experiment on ντ Appearance in the CNGS Neutrino Beam

Ustyuzhanin A.

Physical Review Letters. 2018. Vol. 120. No. 21. P. 211801-1-211801-7.

Article
Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research

Murtagh F., Orlov M. A., Mirkin B.

Journal of Classification. 2018. Vol. 35. No. 1. P. 5-28.

Article
Predictive Model for the Bottomhole Pressure based on Machine Learning
In print

Spesivtsev P., Sinkov K., Sofronov I. et al.

Journal of Petroleum Science and Engineering. 2018.

Article
New and old results on spherical varieties via moduli theory

Roman Avdeev, Cupit-Foutou S.

Advances in Mathematics. 2018. Vol. 328. P. 1299-1352.

Faculty Colloquium: On empirical risk minimization and its variants for statistical learning. Speaker: Quentin Paris, HSE

Event ended

January 23, 18:10 – 19:30 

Quentin Paris, HSE 

On empirical risk minimization and its variants for statistical learning

In this talk, we review fundamental principles of empirical risk minimization and its performance guarantees for statistical learning. We discuss the close interaction with the field of empirical processes and the connection to Vapnik–Chervonenkis combinatorics (including the notion of combinatorial dimension). We present the best known theoretical guarantees for the prediction error of empirical risk minimizers, discuss the limitations of the method, and mention some recent contributions.

Colloquium

Venue:

Moscow, Kochnovsky pr.,3, room 205, 18:10 
Everyone interested is welcome to attend. 
If you need a pass to HSE, please contact computerscience@hse.ru