Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
169 Publications
2023 |
Research Data Reference |
IST-REx-ID: 14995 |
N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, and D.-A. Alistarh, “Lincheck: A practical framework for testing concurrent data structures on JVM.” Zenodo, 2023.
[Published Version]
View
| Files available
| DOI
| Download Published Version (ext.)
2023 |
Published |
Conference Paper |
IST-REx-ID: 14459 |
A. Shevchenko, K. Kögler, H. Hassani, and M. Mondelli, “Fundamental limits of two-layer autoencoders, and achieving them with gradient methods,” in Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, HI, United States, 2023, vol. 202, pp. 31151–31209.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 11180 |
A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “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, Seoul, Republic of Korea, 2022, pp. 353–367.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 11181 |
T. A. Brown, W. Sigouin, and D.-A. Alistarh, “PathCAS: An efficient middle ground for concurrent search data structures,” in Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Seoul, Republic of Korea, 2022, pp. 385–399.
[Published Version]
View
| Files available
| DOI
| WoS
2022 |
Published |
Conference Paper |
IST-REx-ID: 11183 |
A. Nikabadi and J. Korhonen, “Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters,” in 25th International Conference on Principles of Distributed Systems, Strasbourg, France, 2022, vol. 217.
[Published Version]
View
| Files available
| DOI
2022 |
Published |
Conference Paper |
IST-REx-ID: 11184 |
D.-A. Alistarh, R. Gelashvili, and J. Rybicki, “Fast graphical population protocols,” in 25th International Conference on Principles of Distributed Systems, Strasbourg, France, 2022, vol. 217.
[Published Version]
View
| Files available
| DOI
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 11707 |
A. Balliu, J. Hirvonen, D. Melnyk, D. Olivetti, J. Rybicki, and J. Suomela, “Local mending,” in International Colloquium on Structural Information and Communication Complexity, Paderborn, Germany, 2022, vol. 13298, pp. 1–20.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
earlier version | 2022 |
Published |
Conference Paper |
IST-REx-ID: 11844 |
D.-A. Alistarh, J. Rybicki, and S. Voitovych, “Near-optimal leader election in population protocols on graphs,” in Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Salerno, Italy, 2022, pp. 246–256.
[Published Version]
View
| Files available
| DOI
| WoS
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12182 |
M. Pacut, M. Parham, J. Rybicki, S. Schmid, J. Suomela, and A. Tereshchenko, “Brief announcement: Temporal locality in online algorithms,” in 36th International Symposium on Distributed Computing, Augusta, GA, United States, 2022, vol. 246.
[Published Version]
View
| Files available
| DOI
2022 |
Published |
Conference Paper |
IST-REx-ID: 12299 |
E. B. Iofinova, A. Krumes, M. Kurtz, and D.-A. Alistarh, “How well do sparse ImageNet models transfer?,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, LA, United States, 2022, pp. 12256–12266.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 12780 |
I. Markov, H. Ramezanikebrya, and D.-A. Alistarh, “CGX: Adaptive system support for communication-efficient deep learning,” in Proceedings of the 23rd ACM/IFIP International Middleware Conference, Quebec, QC, Canada, 2022, pp. 241–254.
[Published Version]
View
| Files available
| DOI
| WoS
| arXiv
2022 |
Research Data Reference |
IST-REx-ID: 13076 |
A. Postnikova, N. Koval, G. Nadiradze, and D.-A. Alistarh, “Multi-queues can be state-of-the-art priority schedulers.” Zenodo, 2022.
[Published Version]
View
| Files available
| DOI
| Download Published Version (ext.)
2022 |
Published |
Conference Paper |
IST-REx-ID: 17059 |
E. Frantar and D.-A. Alistarh, “SPDY: Accurate pruning with speedup guarantees,” in 39th International Conference on Machine Learning, Baltimore, MD, United States, 2022, vol. 162, pp. 6726–6743.
[Published Version]
View
| Files available
| WoS
2022 |
Published |
Conference Paper |
IST-REx-ID: 17087 |
E. Frantar, S. P. Singh, and D.-A. Alistarh, “Optimal brain compression: A framework for accurate post-training quantization and pruning,” in 36th Conference on Neural Information Processing Systems, New Orleans, LA, United States, 2022, vol. 35.
[Submitted Version]
View
| Files available
| arXiv
2022 |
Published |
Conference Paper |
IST-REx-ID: 17088 |
E. Kurtic et al., “The optimal BERT surgeon: Scalable and accurate second-order pruning for large language models,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates, 2022, pp. 4163–4181.
[Published Version]
View
| Files available
| DOI
| arXiv
2022 |
Published |
Journal Article |
IST-REx-ID: 8286 |
D.-A. Alistarh, G. Nadiradze, and A. Sabour, “Dynamic averaging load balancing on cycles,” Algorithmica, vol. 84, no. 4. Springer Nature, pp. 1007–1029, 2022.
[Published Version]
View
| Files available
| DOI
| WoS
| 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.
[Published Version]
View
| Files available
| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10853 |
A. Fedorov, N. Koval, and D.-A. Alistarh, “A scalable concurrent algorithm for dynamic connectivity,” in Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Virtual, Online, 2021, pp. 208–220.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10854 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 10855 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv