Ilia Markov

10 Publications

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[10]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
Nicolicioiu A, Iofinova EB, Jovanovic A, Kurtic E, Nikdan M, Panferov A, Markov I, Shavit N, Alistarh D-A. 2026. Panza: Investigating the feasibility of fully-local personalized text generation, OpenReview,p.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[9]
2025 | Published | Conference Paper | IST-REx-ID: 20821 | OA
Nguyen AD, Markov I, Wu FZ, Ramezani-Kebrya A, Antonakopoulos K, Alistarh D-A, Cevher V. 2025. Layer-wise quantization for quantized optimistic dual averaging. 42nd International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 267, 46026–46072.
[Published Version] View | Files available | arXiv
 
[8]
2025 | Published | Conference Paper | IST-REx-ID: 20037 | OA
Sawmya S, Kong L, Markov I, Alistarh D-A, Shavit N. 2025. Wasserstein distances, neuronal entanglement, and sparsity. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 26244–26274.
[Published Version] View | Files available | arXiv
 
[7]
2024 | Published | Conference Paper | IST-REx-ID: 17456 | OA
Markov I, Alimohammadi K, Frantar E, Alistarh D-A. 2024. L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. Proceedings of Machine Learning and Systems . MLSys: Machine Learning and Systems vol. 6.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[6]
2024 | Published | Thesis | PhD | IST-REx-ID: 17490 | OA
Markov I. 2024. Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 
[5]
2023 | Published | Conference Paper | IST-REx-ID: 14461 | OA
Markov I, Vladu A, Guo Q, Alistarh D-A. 2023. Quantized distributed training of large models with convergence guarantees. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 24020–24044.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[4]
2022 | Published | Conference Paper | IST-REx-ID: 12780 | OA
Markov I, Ramezanikebrya H, Alistarh D-A. 2022. CGX: Adaptive system support for communication-efficient deep learning. Proceedings of the 23rd ACM/IFIP International Middleware Conference. Middleware: International Middleware Conference, 241–254.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[3]
2021 | Published | Conference Paper | IST-REx-ID: 10049 | OA
Klein K, Pascual Perez G, Walter M, Kamath Hosdurg C, Capretto M, Cueto Noval M, Markov I, Yeo MX, Alwen JF, Pietrzak KZ. 2021. Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. 2021 IEEE Symposium on Security and Privacy . SP: Symposium on Security and Privacy, 268–284.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 
[2]
2021 | Published | Conference Paper | IST-REx-ID: 10432 | OA
Nadiradze G, Markov I, Chatterjee B, Kungurtsev V, Alistarh D-A. 2021. Elastic consistency: A practical consistency model for distributed stochastic gradient descent. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence vol. 35, 9037–9045.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | arXiv
 
[1]
2020 | Published | Conference Paper | IST-REx-ID: 15086 | OA
Faghri F, Tabrizian I, Markov I, Alistarh D-A, Roy D, Ramezani-Kebrya A. 2020. Adaptive gradient quantization for data-parallel SGD. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, NeurIPS, vol. 33.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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10 Publications

Mark all

[10]
2026 | Published | Conference Poster | IST-REx-ID: 21857 | OA
Nicolicioiu A, Iofinova EB, Jovanovic A, Kurtic E, Nikdan M, Panferov A, Markov I, Shavit N, Alistarh D-A. 2026. Panza: Investigating the feasibility of fully-local personalized text generation, OpenReview,p.
[Accepted Version] View | Files available | Download Accepted Version (ext.)
 
[9]
2025 | Published | Conference Paper | IST-REx-ID: 20821 | OA
Nguyen AD, Markov I, Wu FZ, Ramezani-Kebrya A, Antonakopoulos K, Alistarh D-A, Cevher V. 2025. Layer-wise quantization for quantized optimistic dual averaging. 42nd International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 267, 46026–46072.
[Published Version] View | Files available | arXiv
 
[8]
2025 | Published | Conference Paper | IST-REx-ID: 20037 | OA
Sawmya S, Kong L, Markov I, Alistarh D-A, Shavit N. 2025. Wasserstein distances, neuronal entanglement, and sparsity. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 26244–26274.
[Published Version] View | Files available | arXiv
 
[7]
2024 | Published | Conference Paper | IST-REx-ID: 17456 | OA
Markov I, Alimohammadi K, Frantar E, Alistarh D-A. 2024. L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. Proceedings of Machine Learning and Systems . MLSys: Machine Learning and Systems vol. 6.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
[6]
2024 | Published | Thesis | PhD | IST-REx-ID: 17490 | OA
Markov I. 2024. Communication-efficient distributed training of deep neural networks : An algorithms and systems perspective. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 
[5]
2023 | Published | Conference Paper | IST-REx-ID: 14461 | OA
Markov I, Vladu A, Guo Q, Alistarh D-A. 2023. Quantized distributed training of large models with convergence guarantees. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 24020–24044.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
[4]
2022 | Published | Conference Paper | IST-REx-ID: 12780 | OA
Markov I, Ramezanikebrya H, Alistarh D-A. 2022. CGX: Adaptive system support for communication-efficient deep learning. Proceedings of the 23rd ACM/IFIP International Middleware Conference. Middleware: International Middleware Conference, 241–254.
[Published Version] View | Files available | DOI | WoS | arXiv
 
[3]
2021 | Published | Conference Paper | IST-REx-ID: 10049 | OA
Klein K, Pascual Perez G, Walter M, Kamath Hosdurg C, Capretto M, Cueto Noval M, Markov I, Yeo MX, Alwen JF, Pietrzak KZ. 2021. Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. 2021 IEEE Symposium on Security and Privacy . SP: Symposium on Security and Privacy, 268–284.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 
[2]
2021 | Published | Conference Paper | IST-REx-ID: 10432 | OA
Nadiradze G, Markov I, Chatterjee B, Kungurtsev V, Alistarh D-A. 2021. Elastic consistency: A practical consistency model for distributed stochastic gradient descent. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence vol. 35, 9037–9045.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | arXiv
 
[1]
2020 | Published | Conference Paper | IST-REx-ID: 15086 | OA
Faghri F, Tabrizian I, Markov I, Alistarh D-A, Roy D, Ramezani-Kebrya A. 2020. Adaptive gradient quantization for data-parallel SGD. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, NeurIPS, vol. 33.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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Citation Style: ISTA Annual Report

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