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162 Publications

2022 | Published | Conference Paper | IST-REx-ID: 11180 | OA
Postnikova, A., Koval, N., Nadiradze, G., & Alistarh, D.-A. (2022). Multi-queues can be state-of-the-art priority schedulers. In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (pp. 353–367). Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/3503221.3508432
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Research Data Reference | IST-REx-ID: 13076 | OA
Postnikova, A., Koval, N., Nadiradze, G., & Alistarh, D.-A. (2022). Multi-queues can be state-of-the-art priority schedulers. Zenodo. https://doi.org/10.5281/ZENODO.5733408
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2022 | Published | Conference Paper | IST-REx-ID: 17087 | OA
Frantar, E., Singh, S. P., & Alistarh, D.-A. (2022). Optimal brain compression: A framework for accurate post-training quantization and pruning. In 36th Conference on Neural Information Processing Systems (Vol. 35). New Orleans, LA, United States: ML Research Press.
[Submitted Version] View | Files available | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 17059 | OA
Frantar, E., & Alistarh, D.-A. (2022). SPDY: Accurate pruning with speedup guarantees. In 39th International Conference on Machine Learning (Vol. 162, pp. 6726–6743). Baltimore, MD, United States: ML Research Press.
[Published Version] View | Files available | WoS
 
2022 | Published | Conference Paper | IST-REx-ID: 11184 | OA
Alistarh, D.-A., Gelashvili, R., & Rybicki, J. (2022). Fast graphical population protocols. In Q. Bramas, V. Gramoli, & A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems (Vol. 217). Strasbourg, France: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.OPODIS.2021.14
[Published Version] View | Files available | DOI | arXiv
 
2022 | Published | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova, E. B., Krumes, A., Kurtz, M., & Alistarh, D.-A. (2022). How well do sparse ImageNet models transfer? In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 12256–12266). New Orleans, LA, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/cvpr52688.2022.01195
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Published | Journal Article | IST-REx-ID: 8286 | OA
Alistarh, D.-A., Nadiradze, G., & Sabour, A. (2022). Dynamic averaging load balancing on cycles. Algorithmica. Virtual, Online; Germany: Springer Nature. https://doi.org/10.1007/s00453-021-00905-9
[Published Version] View | Files available | DOI | WoS | arXiv
 
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 | Conference Paper | IST-REx-ID: 11844 | OA
Alistarh, D.-A., Rybicki, J., & Voitovych, S. (2022). Near-optimal leader election in population protocols on graphs. In Proceedings of the Annual ACM Symposium on Principles of Distributed Computing (pp. 246–256). Salerno, Italy: Association for Computing Machinery. https://doi.org/10.1145/3519270.3538435
[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: 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: 15267 | OA
Czumaj, A., & Davies, P. (2021). Exploiting spontaneous transmissions for broadcasting and leader election in radio networks. Journal of the ACM. Association for Computing Machinery. https://doi.org/10.1145/3446383
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 9827 | OA
Chatterjee, B., Walulya, I., & Tsigas, P. (2021). Concurrent linearizable nearest neighbour search in LockFree-kD-tree. Theoretical Computer Science. Elsevier. https://doi.org/10.1016/j.tcs.2021.06.041
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
2021 | Published | Conference Paper | IST-REx-ID: 9951
Alistarh, D.-A., Töpfer, M., & Uznański, P. (2021). Comparison dynamics in population protocols. In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing (pp. 55–65). Virtual, Italy: Association for Computing Machinery. https://doi.org/10.1145/3465084.3467915
View | DOI | WoS
 
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: 9678 | OA
Brandt, S., Keller, B., Rybicki, J., Suomela, J., & Uitto, J. (2021). Efficient load-balancing through distributed token dropping. In Annual ACM Symposium on Parallelism in Algorithms and Architectures (pp. 129–139). Virtual Event, United States. https://doi.org/10.1145/3409964.3461785
[Preprint] View | Files available | 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 | 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
 

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