Ilia Markov
Graduate School
Alistarh Group
5 Publications
2023 | Conference Paper | IST-REx-ID: 14461 |
Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044.
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| arXiv
2022 | Conference Paper | IST-REx-ID: 12780 |
Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for communication-efficient deep learning. In: Proceedings of the 23rd ACM/IFIP International Middleware Conference. Association for Computing Machinery; 2022:241-254. doi:10.1145/3528535.3565248
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| arXiv
2021 | Conference Paper | IST-REx-ID: 10432 |
Nadiradze G, Markov I, Chatterjee B, Kungurtsev V, Alistarh D-A. Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. ; 2021:9037-9045.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 10049 |
Klein K, Pascual Perez G, Walter M, et al. Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In: 2021 IEEE Symposium on Security and Privacy . IEEE; 2021:268-284. doi:10.1109/sp40001.2021.00035
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2020 | Conference Paper | IST-REx-ID: 15086 |
Faghri F, Tabrizian I, Markov I, Alistarh D-A, Roy D, Ramezani-Kebrya A. Adaptive gradient quantization for data-parallel SGD. In: Advances in Neural Information Processing Systems. Vol 33. Neural Information Processing Systems Foundation; 2020.
[Preprint]
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| arXiv
5 Publications
2023 | Conference Paper | IST-REx-ID: 14461 |
Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2022 | Conference Paper | IST-REx-ID: 12780 |
Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for communication-efficient deep learning. In: Proceedings of the 23rd ACM/IFIP International Middleware Conference. Association for Computing Machinery; 2022:241-254. doi:10.1145/3528535.3565248
[Published Version]
View
| Files available
| DOI
| arXiv
2021 | Conference Paper | IST-REx-ID: 10432 |
Nadiradze G, Markov I, Chatterjee B, Kungurtsev V, Alistarh D-A. Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. ; 2021:9037-9045.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Conference Paper | IST-REx-ID: 10049 |
Klein K, Pascual Perez G, Walter M, et al. Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In: 2021 IEEE Symposium on Security and Privacy . IEEE; 2021:268-284. doi:10.1109/sp40001.2021.00035
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2020 | Conference Paper | IST-REx-ID: 15086 |
Faghri F, Tabrizian I, Markov I, Alistarh D-A, Roy D, Ramezani-Kebrya A. Adaptive gradient quantization for data-parallel SGD. In: Advances in Neural Information Processing Systems. Vol 33. Neural Information Processing Systems Foundation; 2020.
[Preprint]
View
| Download Preprint (ext.)
| arXiv