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121 Publications

2021 | 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 & Applied Mathematics. https://doi.org/10.1137/20m1366502
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2021 | 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 | 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
 
2020 | Conference Paper | IST-REx-ID: 7272 | OA
Arbel-Raviv, M., Brown, T. A., & Morrison, A. (2020). Getting to the root of concurrent binary search tree performance. In Proceedings of the 2018 USENIX Annual Technical Conference (pp. 295–306). Boston, MA, United States: USENIX Association.
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2020 | Conference Paper | IST-REx-ID: 7605 | OA
Alistarh, D.-A., Fedorov, A., & Koval, N. (2020). In search of the fastest concurrent union-find algorithm. In 23rd International Conference on Principles of Distributed Systems (Vol. 153, p. 15:1-15:16). Neuchatal, Switzerland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.OPODIS.2019.15
[Published Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7803 | OA
Czumaj, A., Davies, P., & Parter, M. (2020). Simple, deterministic, constant-round coloring in the congested clique. In Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing (pp. 309–318). Salerno, Italy: Association for Computing Machinery. https://doi.org/10.1145/3382734.3405751
[Submitted Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 8725 | OA
Aksenov, V., Alistarh, D.-A., Drozdova, A., & Mohtashami, A. (2020). The splay-list: A distribution-adaptive concurrent skip-list. In 34th International Symposium on Distributed Computing (Vol. 179, p. 3:1-3:18). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2020.3
[Published Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9632 | OA
Singh, S. P., & Alistarh, D.-A. (2020). WoodFisher: Efficient second-order approximation for neural network compression. In Advances in Neural Information Processing Systems (Vol. 33, pp. 18098–18109). Vancouver, Canada: Curran Associates.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9631 | OA
Aksenov, V., Alistarh, D.-A., & Korhonen, J. (2020). Scalable belief propagation via relaxed scheduling. In Advances in Neural Information Processing Systems (Vol. 33, pp. 22361–22372). Vancouver, Canada: Curran Associates.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9415 | OA
Kurtz, M., Kopinsky, J., Gelashvili, R., Matveev, A., Carr, J., Goin, M., … Alistarh, D.-A. (2020). Inducing and exploiting activation sparsity for fast neural network inference. In 37th International Conference on Machine Learning, ICML 2020 (Vol. 119, pp. 5533–5543). Online.
[Published Version] View | Files available
 

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