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5 Publications
2023 | Published | Journal Article | IST-REx-ID: 14815 | 
A. Beznosikov, S. Horvath, P. Richtarik, and M. Safaryan, “On biased compression for distributed learning,” Journal of Machine Learning Research, vol. 24. Journal of Machine Learning Research, pp. 1–50, 2023.
[Published Version]
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| WoS
| arXiv
2022 | Published | Journal Article | IST-REx-ID: 10802 |
N. H. Konstantinov and C. Lampert, “Fairness-aware PAC learning from corrupted data,” Journal of Machine Learning Research, vol. 23. ML Research Press, pp. 1–60, 2022.
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| arXiv
2022 | Published | Journal Article | IST-REx-ID: 11420 |
A. Shevchenko, V. Kungurtsev, and M. Mondelli, “Mean-field analysis of piecewise linear solutions for wide ReLU networks,” Journal of Machine Learning Research, vol. 23, no. 130. Journal of Machine Learning Research, pp. 1–55, 2022.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 10180 |
T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, and A. Krumes, “Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,” Journal of Machine Learning Research, vol. 22, no. 241. ML Research Press, pp. 1–124, 2021.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 9571 |
A. Ramezani-Kebrya, F. Faghri, I. Markov, V. Aksenov, D.-A. Alistarh, and D. M. Roy, “NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization,” Journal of Machine Learning Research, vol. 22, no. 114. Journal of Machine Learning Research, p. 1−43, 2021.
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| arXiv