Nikita Puchkin
- Senior Research Fellow:Faculty of Computer Science / AI and Digital Science Institute / International Laboratory of Stochastic Algorithms and High-Dimensional Inference
- Lecturer:Faculty of Computer Science / Department of Complex System Modelling Technologies
- Nikita Puchkin has been at HSE University since 2018.
Education and Degrees
- 2023
Candidate of Sciences* (PhD)
HSE University - 2018
Master's in Applied Mathematics and Applied Physics
Moscow Institute of Physics and Technology - 2016
Bachelor's
Moscow Institute of Physics and Technology
* Candidate of Sciences
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
Courses (2023/2024)
- Mathematical Statistics (advanced course) (Bachelor’s programme; Faculty of Computer Science; 2 year, 3, 4 module)Rus
- Past Courses
Courses (2022/2023)
- High Dimensional Probability and Statistics (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Mathematical Statistics (advanced course) (Bachelor’s programme; Faculty of Computer Science; 2 year, 3, 4 module)Rus
- Random Matrix Theory (Master’s programme; Faculty of Computer Science; 2 year, 1 module)Eng
Publications11
- Chapter Puchkin N., Gorbunov E., Kutuzov N., Gasnikov A. Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2-4 May 2024, Palau de Congressos, Valencia, Spain. PMLR: Volume 238 Vol. 238. Valencia : PMLR, 2024. P. 856-864.
- Article Puchkin N., Samsonov S., Belomestny D., Moulines E., Naumov A. Rates of convergence for density estimation with generative adversarial networks // Journal of Machine Learning Research. 2024. Vol. 25. No. 29. P. 1-47.
- Article Nikita Puchkin, Vladimir Spokoiny, Eugene Stepanov, Trevisan D. Reconstruction of manifold embeddings into Euclidean spaces via intrinsic distances // ESAIM - Control, Optimisation and Calculus of Variations. 2024. Vol. 30. Article 3. doi
- Chapter Puchkin N., Shcherbakova V. A Contrastive Approach to Online Change Point Detection, in: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Volume 206 Vol. 206. Valencia : PMLR, 2023. P. 5686-5713.
- Chapter Puchkin N., Zhivotovskiy N. Exploring Local Norms in Exp-concave Statistical Learning, in: Proceedings of Machine Learning Research: Volume 195: The Thirty Sixth Annual Conference on Learning Theory, 12-15 July 2023, Bangalore, India Vol. 195: The Thirty Sixth Annual Conference on Learning Theory, 12-15 July 2023, Bangalore, India. PMLR, 2023. P. 1993-2013.
- Article Nikita Puchkin, Vladimir Ulyanov. Inference via randomized test statistics // Annales de l'institut Henri Poincare (B) Probability and Statistics. 2023. Vol. 59. No. 3. P. 1508-1529. doi
- Article Belomestny D., Naumov A., Puchkin N., Samsonov S. Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations // Neural Networks. 2023. Vol. 161. P. 242-253. doi
- Article Puchkin N., Zhivotovskiy N. Exponential Savings in Agnostic Active Learning through Abstention // IEEE Transactions on Information Theory. 2022. Vol. 68. No. 7. P. 4651-4665. doi
- Article Puchkin N., Spokoiny V. Structure-adaptive Manifold Estimation // Journal of Machine Learning Research. 2022. Vol. 23. No. 40. P. 1-62.
- Chapter Puchkin N., Zhivotovskiy N. Exponential savings in agnostic active learning through abstention, in: Proceedings of Machine Learning Research Vol. 134: Conference on Learning Theory. PMLR, 2021. P. 3806-3832.
- Article Puchkin N., Spokoiny V. An adaptive multiclass nearest neighbor classifier // ESAIM: Probability and Statistics. 2020. Vol. 24. P. 69-99. doi
Conferences
2018
12th International Vilnius Conference on Probability Theory and Mathematical Statistics and 2018 IMS Annual Meeting on Probability and Statistics (Вильнюс). Presentation: Pointwise adaptation via stagewise aggregation of local estimates for multiclass classification (poster presentation)HSE Faculty of Computer Science and Skoltech Hold Math of Machine Learning Olympiad 2022
HSE's Faculty of Computer Science and the Skolkovo Institute of Science and Technology have held the Mathematics of Machine Learning Olympiad for the fifth time. The participants competed for prizes and the opportunity to matriculate at two universities without exams by enrolling in the HSE and Skoltech joint master's programme in Math of Machine Learning.
HDI Lab staff attend International Vilnius Conference on Probability Theory and Mathematical Statistics 2018
12th International Vilnius Conference on Probability Theory and Mathematical Statistics and 2018 IMS Annual Meeting on Probability and Statistics took place in Vilnius (Lithuania) on July 2-6. This is one of the world's leading conferences in the field of modern probability theory and mathematical statistics, which is held every four years since 1973. This year over 200 works were presented at the event and 500 participants from all over the globe attended it.