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Conference and Workshop Papers
- 2021
[c5]Dmitry Medvedev, Alexander D'yakonov:
Learning to Generate Synthetic Training Data Using Gradient Matching and Implicit Differentiation. AIST (Supplement) 2021: 138-150- 2020
- [c4]Dmitry Medvedev, Alexander D'yakonov:
New Properties of the Data Distillation Method When Working with Tabular Data. AIST 2020: 379-390 - 2017
- [c3]Alexander D'yakonov, Anastasia Golovina:
Выявление аномалий в работе механизмов методами машинного обучения (Anomaly Detection in Mechanisms Using Machine Learning). DAMDID/RCDL 2017: 389-396 - 2014
- [c2]Grigorios Tsoumakas, Apostolos Papadopoulos, Weining Qian, Stavros Vologiannidis, Alexander D'yakonov, Antti Puurula, Jesse Read, Jan Svec, Stanislav Semenov:
WISE 2014 Challenge: Multi-label Classification of Print Media Articles to Topics. WISE (2) 2014: 541-548 - 2012
- [c1]Alexander D'yakonov:
A Blending of Simple Algorithms for Topical Classification. RSCTC 2012: 432-438
Informal and Other Publications
- 2023
- [i4]Ruslan Vasilev
, Alexander D'yakonov:
Calibration of Neural Networks. CoRR abs/2303.10761 (2023) - 2022
- [i3]Dmitry Medvedev, Alexander D'yakonov:
Learning to Generate Synthetic Training Data using Gradient Matching and Implicit Differentiation. CoRR abs/2203.08559 (2022) - 2020
- [i2]Dmitry Medvedev, Alexander D'yakonov:
New Properties of the Data Distillation Method When Working With Tabular Data. CoRR abs/2010.09839 (2020) - 2019
- [i1]Sergey Ivanov, Alexander D'yakonov:
Modern Deep Reinforcement Learning Algorithms. CoRR abs/1906.10025 (2019)
Coauthor Index
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