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ORCIDDmitry Yarotsky
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2020 – today
- 2024
[j11]Maksim Velikanov, Dmitry Yarotsky:
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions. J. Mach. Learn. Res. 25: 81:1-81:78 (2024)- [c20]Maksim Velikanov, Maxim Panov, Dmitry Yarotsky:
Generalization error of spectral algorithms. ICLR 2024 - [i19]Dmitry Yarotsky:
Learning high-dimensional targets by two-parameter models and gradient flow. CoRR abs/2402.17089 (2024) - [i18]Maksim Velikanov, Maxim Panov, Dmitry Yarotsky:
Generalization error of spectral algorithms. CoRR abs/2403.11696 (2024) - [i17]Dmitry Yarotsky, Maksim Velikanov:
SGD with memory: fundamental properties and stochastic acceleration. CoRR abs/2410.04228 (2024) - 2023
- [j10]Vladislav Molodtsov, Roman Bychkov
, Alexander Osinsky, Dmitry Yarotsky, Andrey Ivanov:
Beamspace Selection in Multi-User Massive MIMO. IEEE Access 11: 18761-18771 (2023) - [j9]Vladislav Molodtsov, Roman Bychkov, Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Training FFT to Select Beams in Massive MIMO. IEEE Wirel. Commun. Lett. 12(6): 1017-1021 (2023) - [c19]Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky:
A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. ICLR 2023 - [c18]Dmitry Yarotsky:
Structure of universal formulas. NeurIPS 2023 - [i16]Dmitry Yarotsky:
Structure of universal formulas. CoRR abs/2311.03910 (2023) - 2022
- [c17]Maksim Velikanov, Roman V. Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky:
Embedded Ensembles: infinite width limit and operating regimes. AISTATS 2022: 3138-3163 - [i15]Maksim Velikanov, Dmitry Yarotsky:
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions. CoRR abs/2202.00992 (2022) - [i14]Maksim Velikanov, Roman Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev, Dmitry Yarotsky:
Embedded Ensembles: Infinite Width Limit and Operating Regimes. CoRR abs/2202.12297 (2022) - [i13]Maksim Velikanov, Denis Kuznedelev, Dmitry Yarotsky:
A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta. CoRR abs/2206.11124 (2022) - 2021
- [j8]Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Efficient Performance Bound for Channel Estimation in Massive MIMO Receiver. IEEE Trans. Wirel. Commun. 20(11): 7001-7010 (2021) - [j7]Alexander Osinsky, Andrey Ivanov, Dmitry Lakontsev, Dmitry Yarotsky:
Lower Performance Bound for Beamspace Channel Estimation in Massive MIMO. IEEE Wirel. Commun. Lett. 10(2): 311-314 (2021) - [j6]Aleksei Kalinov, Roman Bychkov, Andrey Ivanov, Alexander Osinsky, Dmitry Yarotsky:
Machine Learning-Assisted PAPR Reduction in Massive MIMO. IEEE Wirel. Commun. Lett. 10(3): 537-541 (2021) - [c16]Dmitry Yarotsky:
Elementary superexpressive activations. ICML 2021: 11932-11940 - [c15]Maksim Velikanov, Dmitry Yarotsky:
Explicit loss asymptotics in the gradient descent training of neural networks. NeurIPS 2021: 2570-2582 - [c14]Roman Bychkov, Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Data-Driven Beams Selection for Beamspace Channel Estimation in Massive MIMO. VTC Spring 2021: 1-5 - [c13]Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Spatial Denoising for Sparse Channel Estimation in Coherent Massive MIMO. VTC Fall 2021: 1-5 - [c12]Alexander Osinsky, Roman Bychkov, Andrey Ivanov, Dmitry Yarotsky:
Adaptive Channel Interpolation in High-Speed Massive MIMO. VTC Spring 2021: 1-5 - [c11]Dmitry Yarotsky, Andrey Ivanov, Roman Bychkov, Alexander Osinsky, Andrey Savinov, Mikhail Trefilov, Vladimir Lyashev:
Machine Learning-Assisted Channel Estimation in Massive MIMO Receiver. VTC Spring 2021: 1-5 - [i12]Dmitry Yarotsky:
Elementary superexpressive activations. CoRR abs/2102.10911 (2021) - [i11]Maksim Velikanov, Dmitry Yarotsky:
Universal scaling laws in the gradient descent training of neural networks. CoRR abs/2105.00507 (2021) - 2020
- [j5]Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Bayesian Approach to Channel Interpolation in Massive MIMO Receiver. IEEE Commun. Lett. 24(12): 2751-2755 (2020) - [c10]Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky:
Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO. ICASSP 2020: 4925-4929 - [c9]Ivan Anokhin, Dmitry Yarotsky:
Low-loss connection of weight vectors: distribution-based approaches. ICML 2020: 335-344 - [c8]Dmitry Yarotsky, Anton Zhevnerchuk:
The phase diagram of approximation rates for deep neural networks. NeurIPS 2020 - [c7]Andrey Ivanov, Alexander Osinsky, Dmitry Lakontsev, Dmitry Yarotsky:
High Performance Interference Suppression in Multi-User Massive MIMO Detector. VTC Spring 2020: 1-5 - [c6]Alexander Osinsky, Andrey Ivanov, Dmitry Lakontsev, Roman Bychkov, Dmitry Yarotsky:
Data-Aided LS Channel Estimation in Massive MIMO Turbo-Receiver. VTC Spring 2020: 1-5 - [i10]Andrey Ivanov, Alexander Osinsky, Dmitry Lakontsev, Dmitry Yarotsky:
High Performance Interference Suppression in Multi-User Massive MIMO Detector. CoRR abs/2005.03466 (2020) - [i9]Ivan Anokhin, Dmitry Yarotsky:
Low-loss connection of weight vectors: distribution-based approaches. CoRR abs/2008.00741 (2020)
2010 – 2019
- 2019
- [c5]Andrey Ivanov, Andrey Savinov, Dmitry Yarotsky:
Iterative Nonlinear Detection and Decoding in Multi-User Massive MIMO. IWCMC 2019: 573-578 - [i8]Dmitry Yarotsky, Anton Zhevnerchuk:
The phase diagram of approximation rates for deep neural networks. CoRR abs/1906.09477 (2019) - 2018
- [c4]Dmitry Yarotsky:
Optimal approximation of continuous functions by very deep ReLU networks. COLT 2018: 639-649 - [c3]Andrey Ivanov, Artyom Volokhatyi, Dmitry Lakontsev, Dmitry Yarotsky:
Unused Beam Reservation for PAPR Reduction in Massive MIMO System. VTC Spring 2018: 1-5 - [c2]Andrey Ivanov, Dmitry Yarotsky, Maria Stoliarenko, Alexey A. Frolov:
Smart Sorting in Massive MIMO Detection. WiMob 2018: 1-6 - [i7]Dmitry Yarotsky:
Optimal approximation of continuous functions by very deep ReLU networks. CoRR abs/1802.03620 (2018) - [i6]Dmitry Yarotsky:
Universal approximations of invariant maps by neural networks. CoRR abs/1804.10306 (2018) - [i5]Dmitry Yarotsky:
Collective evolution of weights in wide neural networks. CoRR abs/1810.03974 (2018) - 2017
- [j4]Dmitry Yarotsky:
Error bounds for approximations with deep ReLU networks. Neural Networks 94: 103-114 (2017) - [c1]Evgeni Bikov, Pavel Boyko, Evgeny Sokolov, Dmitry Yarotsky:
Railway Incident Ranking with Machine Learning. ICMLA 2017: 601-606 - [i4]Dmitry Yarotsky:
Geometric features for voxel-based surface recognition. CoRR abs/1701.04249 (2017) - [i3]Dmitry Yarotsky:
Quantified advantage of discontinuous weight selection in approximations with deep neural networks. CoRR abs/1705.01365 (2017) - 2016
- [j3]Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky:
GTApprox: Surrogate modeling for industrial design. Adv. Eng. Softw. 102: 29-39 (2016) - [i2]Mikhail Belyaev, Evgeny Burnaev, Ermek Kapushev, Maxim Panov, Pavel V. Prikhodko, Dmitry P. Vetrov, Dmitry Yarotsky:
GTApprox: surrogate modeling for industrial design. CoRR abs/1609.01088 (2016) - [i1]Dmitry Yarotsky:
Error bounds for approximations with deep ReLU networks. CoRR abs/1610.01145 (2016) - 2013
- [j2]Dmitry Yarotsky:
Univariate interpolation by exponential functions and Gaussian RBFs for generic sets of nodes. J. Approx. Theory 166: 163-175 (2013) - [j1]Dmitry Yarotsky:
Examples of inconsistency in optimization by expected improvement. J. Glob. Optim. 56(4): 1773-1790 (2013)
Coauthor Index
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