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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.

Industry Webinar: Human and ML — Collaboration in Data Labeling

18+
*recommended age
Event ended

In this webinar, we will consider an approach to the formation of high-quality data using a scalable crowdsourcing approach. Data quality in the current pipeline of creating AI products is an important component along with computing power (such as GPU, TPU, etc) and “algorithms” for data transformation (in fact, machine learning methods). However, stable markup of high-quality data is a complex and not scalable approach. We will look at how you can combine knowledge from current state-of-the-art models to aggregate, construct the correct answer, create dynamically calculated prior knowledge about the correct labels, apply human verdicts to improve and accelerate the receipt of correctly annotated data.

Join Evgenii Sorokin (Machine Learning Engineer from Toloka) on Wednesday, December 15, to learn more about human and ML collaboration on data labelling. Participants will have an opportunity to ask questions, so come prepared to engage!

Please register following the link