Kirill O. Neklyudov
- Postgraduate Student:Faculty of Computer Science / Big Data and Information Retrieval School
- Visiting Scholar:Faculty of Computer Science / Big Data and Information Retrieval School / Joint Department with Yandex
- Research Fellow:Faculty of Computer Science / Big Data and Information Retrieval School / Samsung-HSE Laboratory
- Kirill O. Neklyudov has been at HSE since 2016.
Continuing education / Professional retraining / Internships / Study abroad experience
Yandex School of Data Analysis (2014-2016), big data department
Intern, Yandex (november 2013 - june 2014)
Postgraduate Studies
2nd year of study
Approved topic of thesis: Differentiable architectures for neural networks
Academic Supervisor: Vetrov, Dmitry
Courses (2017/2018)
- Bayesian Machine Learning (Bachelor’s programme; Faculty of Computer Science; programme "Applied Mathematics and Information Science"; 4 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; programme "Applied Mathematics and Information Science"; 3 year, 1, 2 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; programme "Applied Mathematics and Information Science"; 3 year, 3, 4 module)Rus
Publications1
Chapter Neklyudov K. O., Molchanov D., Ashukha A., Vetrov D. Structured Bayesian Pruning via Log-Normal Multiplicative Noise, in: Advances in Neural Information Processing Systems 30 (NIPS 2017). Montreal : Curran Associates, 2017. P. 1-10.
How to Adjust a Smaller Size Neural Network without Quality Loss
Staff members of the HSE Faculty of Computer Science recently presented their papers at the biggest international conference on machine learning, Neural Information Processing Systems (NIPS)’.
How to Adjust a Smaller Size Neural Network without Quality Loss
Staff members of the HSE Faculty of Computer Science recently presented their papers at the biggest international conference on machine learning, Neural Information Processing Systems (NIPS)’.
