Ilia Markov
Graduate School
Alistarh Group
7 Publications
2024 | Published | Thesis | IST-REx-ID: 17490 | 
Markov, Ilia. Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17490.
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2024 | Published | Conference Paper | IST-REx-ID: 17456 |
Markov, Ilia, et al. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” Proceedings of Machine Learning and Systems , edited by P. Gibbons et al., vol. 6, Association for Computing Machinery, 2024.
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2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov, Ilia, et al. “Quantized Distributed Training of Large Models with Convergence Guarantees.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 24020–44.
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2022 | Published | Conference Paper | IST-REx-ID: 12780 |
Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–54, doi:10.1145/3528535.3565248.
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2021 | Published | Conference Paper | IST-REx-ID: 10432 |
Nadiradze, Giorgi, et al. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 10, 2021, pp. 9037–45.
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2021 | Published | Conference Paper | IST-REx-ID: 10049 |
Klein, Karen, et al. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” 2021 IEEE Symposium on Security and Privacy , IEEE, 2021, pp. 268–84, doi:10.1109/sp40001.2021.00035.
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2020 | Published | Conference Paper | IST-REx-ID: 15086 |
Faghri, Fartash, et al. “Adaptive Gradient Quantization for Data-Parallel SGD.” Advances in Neural Information Processing Systems, vol. 33, Neural Information Processing Systems Foundation, 2020.
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Grants
7 Publications
2024 | Published | Thesis | IST-REx-ID: 17490 |
Markov, Ilia. Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17490.
[Published Version]
View
| Files available
| DOI
2024 | Published | Conference Paper | IST-REx-ID: 17456 |
Markov, Ilia, et al. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” Proceedings of Machine Learning and Systems , edited by P. Gibbons et al., vol. 6, Association for Computing Machinery, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov, Ilia, et al. “Quantized Distributed Training of Large Models with Convergence Guarantees.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 24020–44.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12780 |
Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–54, doi:10.1145/3528535.3565248.
[Published Version]
View
| Files available
| DOI
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10432 |
Nadiradze, Giorgi, et al. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 10, 2021, pp. 9037–45.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10049 |
Klein, Karen, et al. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” 2021 IEEE Symposium on Security and Privacy , IEEE, 2021, pp. 268–84, doi:10.1109/sp40001.2021.00035.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2020 | Published | Conference Paper | IST-REx-ID: 15086 |
Faghri, Fartash, et al. “Adaptive Gradient Quantization for Data-Parallel SGD.” Advances in Neural Information Processing Systems, vol. 33, Neural Information Processing Systems Foundation, 2020.
[Preprint]
View
| Download Preprint (ext.)
| arXiv