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Dan Alistarh

Jiale Chen

Vage Egiazarian

Eldar Kurtic

Ionut-Vlad Modoranu

Mahdi Nikdan

Andrei Panferov

Sergei Pankratov

Ileana Rugina

Erik Schultheis

Soroush Tabesh

Alexandra Volkova

Filipp Zmushko

Sharareh Alipour

Vitalii Aksenov

Trevor Brown

Bapi Chatterjee

Elvir Crncevic

Peter Davies

Alexander Fedorov

Elias Frantar

Janne Korhonen

Roberto Lopez Castro

Ilia Markov

Giorgi Nadiradze

Alexandra Krumes

Joel Rybicki

Mher Safaryan

Sidak Singh

Martin Töpfer

Sokolova, Mariia



174 Publications

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. In Proceedings of the 23rd ACM/IFIP International Middleware Conference (pp. 241–254). Quebec, QC, Canada: Association for Computing Machinery. https://doi.org/10.1145/3528535.3565248
[Published Version] View | Files available | DOI | WoS | arXiv
 
2022 | Published | Journal Article | IST-REx-ID: 11420 | OA
Shevchenko, A., Kungurtsev, V., & Mondelli, M. (2022). Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. Journal of Machine Learning Research.
[Published Version] View | Files available | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10853 | OA
Fedorov, A., Koval, N., & Alistarh, D.-A. (2021). A scalable concurrent algorithm for dynamic connectivity. In Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures (pp. 208–220). Virtual, Online: Association for Computing Machinery. https://doi.org/10.1145/3409964.3461810
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10854 | OA
Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems (pp. 71–72). Virtual, Online: Association for Computing Machinery. https://doi.org/10.1145/3410220.3453923
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 10855 | OA
Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3447384
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11458 | OA
Krumes, A., Iofinova, E. B., Vladu, A., & Alistarh, D.-A. (2021). AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 8557–8570). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11463 | OA
Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free approximations of second-order information. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11464 | OA
Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower bounds for distributed optimisation. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 13147 | OA
Alimisis, F., Davies, P., & Alistarh, D.-A. (2021). Communication-efficient distributed optimization with quantized preconditioners. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 196–206). Virtual: ML Research Press.
[Published Version] View | Files available | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 15263 | OA
Alimisis, F., Orvieto, A., Becigneul, G., & Lucchi, A. (2021). Momentum improves optimization on Riemannian manifolds. In Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (Vol. 130, pp. 1351–1359). San Diego, CA, United States; Virtual: ML Research Press.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 15271
Czumaj, A., Davies, P., & Parter, M. (2021). Simple, deterministic, constant-round coloring in congested clique and MPC. SIAM Journal on Computing. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/20m1366502
View | DOI | WoS
 
2021 | Published | Journal Article | IST-REx-ID: 10180 | OA
Hoefler, T., Alistarh, D.-A., Ben-Nun, T., Dryden, N., & Krumes, A. (2021). Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks. Journal of Machine Learning Research. ML Research Press.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10216 | OA
Chatterjee, B., Peri, S., & Sa, M. (2021). Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.52
[Published Version] View | Files available | DOI | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10217 | OA
Alistarh, D.-A., Gelashvili, R., & Nadiradze, G. (2021). Lower bounds for shared-memory leader election under bounded write contention. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.4
[Published Version] View | Files available | DOI
 
2021 | Published | Conference Paper | IST-REx-ID: 10218 | OA
Alistarh, D.-A., Gelashvili, R., & Rybicki, J. (2021). Brief announcement: Fast graphical population protocols. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.43
[Published Version] View | Files available | DOI | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10219 | OA
Korhonen, J., Paz, A., Rybicki, J., Schmid, S., & Suomela, J. (2021). Brief announcement: Sinkless orientation is hard also in the supported LOCAL model. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.58
[Published Version] View | Files available | DOI | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10435 | OA
Nadiradze, G., Sabour, A., Davies, P., Li, S., & Alistarh, D.-A. (2021). Asynchronous decentralized SGD with quantized and local updates. In 35th Conference on Neural Information Processing Systems. Sydney, Australia: Neural Information Processing Systems Foundation.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 7939 | OA
Censor-Hillel, K., Dory, M., Korhonen, J., & Leitersdorf, D. (2021). Fast approximate shortest paths in the congested clique. Distributed Computing. Springer Nature. https://doi.org/10.1007/s00446-020-00380-5
[Published Version] View | Files available | DOI | Download Published Version (ext.) | WoS | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 8723 | OA
Li, S., Tal Ben-Nun, T. B.-N., Nadiradze, G., Girolamo, S. D., Dryden, N., Alistarh, D.-A., & Hoefler, T. (2021). Breaking (global) barriers in parallel stochastic optimization with wait-avoiding group averaging. IEEE Transactions on Parallel and Distributed Systems. IEEE. https://doi.org/10.1109/TPDS.2020.3040606
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 9541 | OA
Czumaj, A., Davies, P., & Parter, M. (2021). Graph sparsification for derandomizing massively parallel computation with low space. ACM Transactions on Algorithms. Association for Computing Machinery. https://doi.org/10.1145/3451992
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | WoS | arXiv
 

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