Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
121 Publications
2022 | 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 | 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 | 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
2022 | Conference Paper | IST-REx-ID: 12299 |
E. B. Iofinova, E.-A. Peste, 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
2021 | Journal Article | IST-REx-ID: 10180 |
T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, and E.-A. Peste, “Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,” Journal of Machine Learning Research, vol. 22, no. 241. Journal of Machine Learning Research, pp. 1–124, 2021.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv