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ORCIDEkaterina Lobacheva
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2020 – today
- 2024
[c11]Ildus Sadrtdinov, Maxim Kodryan, Eduard Pokonechny, Ekaterina Lobacheva, Dmitry P. Vetrov:
Where Do Large Learning Rates Lead Us? NeurIPS 2024- [i15]Ildus Sadrtdinov, Maxim Kodryan, Eduard Pokonechny, Ekaterina Lobacheva, Dmitry P. Vetrov:
Where Do Large Learning Rates Lead Us? CoRR abs/2410.22113 (2024) - 2023
- [c10]Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva:
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning. NeurIPS 2023 - [i14]Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva:
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning. CoRR abs/2303.03374 (2023) - [i13]Ekaterina Lobacheva, Eduard Pockonechnyy, Maxim Kodryan, Dmitry P. Vetrov:
Large Learning Rates Improve Generalization: But How Large Are We Talking About? CoRR abs/2311.11303 (2023) - 2022
- [c9]Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov:
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. NeurIPS 2022 - [i12]Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov:
Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. CoRR abs/2209.03695 (2022) - 2021
- [c8]Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov:
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. NeurIPS 2021: 21545-21556 - [i11]Ekaterina Lobacheva, Maxim Kodryan, Nadezhda Chirkova, Andrey Malinin, Dmitry P. Vetrov:
On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay. CoRR abs/2106.15739 (2021) - [i10]Ildus Sadrtdinov, Nadezhda Chirkova, Ekaterina Lobacheva:
On the Memorization Properties of Contrastive Learning. CoRR abs/2107.10143 (2021) - [i9]Evgeny Bobrov, Sergey Troshin, Nadezhda Chirkova, Ekaterina Lobacheva, Sviatoslav Panchenko, Dmitry P. Vetrov, Dmitry Kropotov:
Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems. CoRR abs/2112.14423 (2021) - 2020
- [c7]Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov:
Structured Sparsification of Gated Recurrent Neural Networks. AAAI 2020: 4989-4996 - [c6]Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov:
On Power Laws in Deep Ensembles. NeurIPS 2020 - [i8]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? CoRR abs/2005.07292 (2020) - [i7]Ekaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov:
On Power Laws in Deep Ensembles. CoRR abs/2007.08483 (2020)
2010 – 2019
- 2019
- [i6]Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry P. Vetrov:
Structured Sparsification of Gated Recurrent Neural Networks. CoRR abs/1911.05585 (2019) - 2018
- [c5]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Bayesian Compression for Natural Language Processing. EMNLP 2018: 2910-2915 - [c4]Alexander Chistyakov, Ekaterina Lobacheva, Alexander Shevelev, Alexey Romanenko:
Monotonic models for real-time dynamic malware detection. ICLR (Workshop) 2018 - [i5]Alexander Chistyakov, Ekaterina Lobacheva, Arseny Kuznetsov, Alexey Romanenko:
Semantic embeddings for program behavior patterns. CoRR abs/1804.03635 (2018) - [i4]Alexander Chistyakov, Ekaterina Lobacheva, Alexander Shevelev, Alexey Romanenko:
Monotonic models for real-time dynamic malware detection. CoRR abs/1804.03643 (2018) - [i3]Nadezhda Chirkova, Ekaterina Lobacheva, Dmitry P. Vetrov:
Bayesian Compression for Natural Language Processing. CoRR abs/1810.10927 (2018) - [i2]Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov:
Bayesian Sparsification of Gated Recurrent Neural Networks. CoRR abs/1812.05692 (2018) - 2017
- [c3]Alexander Chistyakov, Ekaterina Lobacheva, Arseny Kuznetsov, Alexey Romanenko:
Semantic embeddings for program behaviour patterns. ICLR (Workshop) 2017 - [i1]Ekaterina Lobacheva, Nadezhda Chirkova, Dmitry P. Vetrov:
Bayesian Sparsification of Recurrent Neural Networks. CoRR abs/1708.00077 (2017) - 2016
- [c2]Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry P. Vetrov:
Deep Part-Based Generative Shape Model with Latent Variables. BMVC 2016 - 2015
- [c1]Ekaterina Lobacheva, Olga Veksler, Yuri Boykov:
Joint Optimization of Segmentation and Color Clustering. ICCV 2015: 1626-1634
Coauthor Index
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