Alexander Shevchenko
Graduate School
Mondelli Group
5 Publications
2024 | Published | Thesis | IST-REx-ID: 17465 | 
Shevchenko, Alexander. “High-Dimensional Limits in Artificial Neural Networks.” Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:17465.
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2024 | Published | Conference Paper | IST-REx-ID: 17469 |
Kögler, Kevin, Alexander Shevchenko, Hamed Hassani, and Marco Mondelli. “Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth.” In Proceedings of the 41st International Conference on Machine Learning, 235:24964–15. ML Research Press, 2024.
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2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, Alexander, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.
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2022 | Published | Journal Article | IST-REx-ID: 11420 |
Shevchenko, Alexander, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2022.
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2020 | Published | Conference Paper | IST-REx-ID: 9198 |
Shevchenko, Aleksandr, and Marco Mondelli. “Landscape Connectivity and Dropout Stability of SGD Solutions for Over-Parameterized Neural Networks.” In Proceedings of the 37th International Conference on Machine Learning, 119:8773–84. ML Research Press, 2020.
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5 Publications
2024 | Published | Thesis | IST-REx-ID: 17465 |
Shevchenko, Alexander. “High-Dimensional Limits in Artificial Neural Networks.” Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:17465.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 17469 |
Kögler, Kevin, Alexander Shevchenko, Hamed Hassani, and Marco Mondelli. “Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth.” In Proceedings of the 41st International Conference on Machine Learning, 235:24964–15. ML Research Press, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, Alexander, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2022 | Published | Journal Article | IST-REx-ID: 11420 |
Shevchenko, Alexander, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2022.
[Published Version]
View
| Files available
| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 9198 |
Shevchenko, Aleksandr, and Marco Mondelli. “Landscape Connectivity and Dropout Stability of SGD Solutions for Over-Parameterized Neural Networks.” In Proceedings of the 37th International Conference on Machine Learning, 119:8773–84. ML Research Press, 2020.
[Published Version]
View
| Files available
| arXiv