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.
122 Publications
2021 | Conference Paper | IST-REx-ID: 13147 | 
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 | Journal Article | IST-REx-ID: 8723 |
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 | Journal Article | IST-REx-ID: 9827 |
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 | 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 | Conference Paper | IST-REx-ID: 9935 |
Czumaj, A., Davies, P., & Parter, M. (2021). Improved deterministic (Δ+1) coloring in low-space MPC. In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing (pp. 469–479). Virtual, Italy: Association for Computing Machinery. https://doi.org/10.1145/3465084.3467937
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2021 | Conference Paper | IST-REx-ID: 9933 |
Czumaj, A., Davies, P., & Parter, M. (2021). Component stability in low-space massively parallel computation. In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing (pp. 481–491). Virtual, Italy: Association for Computing Machinery. https://doi.org/10.1145/3465084.3467903
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
| arXiv
2021 | Conference Paper | IST-REx-ID: 10432 |
Nadiradze, G., Markov, I., Chatterjee, B., Kungurtsev, V., & Alistarh, D.-A. (2021). Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 9037–9045). Virtual.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Conference Paper | IST-REx-ID: 10049 |
Klein, K., Pascual Perez, G., Walter, M., Kamath Hosdurg, C., Capretto, M., Cueto Noval, M., … Pietrzak, K. Z. (2021). Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In 2021 IEEE Symposium on Security and Privacy (pp. 268–284). San Francisco, CA, United States: IEEE. https://doi.org/10.1109/sp40001.2021.00035
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2021 | Conference Paper | IST-REx-ID: 10854 |
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 | Journal Article | IST-REx-ID: 10855 |
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 | Thesis | IST-REx-ID: 10429 |
Nadiradze, G. (2021). On achieving scalability through relaxation. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10429
[Published Version]
View
| Files available
| DOI
2021 | Conference Paper | IST-REx-ID: 10435 |
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 | Journal Article | IST-REx-ID: 9541 |
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
2021 | Conference Paper | IST-REx-ID: 9678 |
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 | Journal Article | IST-REx-ID: 9571 |
Ramezani-Kebrya, A., Faghri, F., Markov, I., Aksenov, V., Alistarh, D.-A., & Roy, D. M. (2021). NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization. Journal of Machine Learning Research. Journal of Machine Learning Research.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Journal Article | IST-REx-ID: 7939 |
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 | 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
View
| DOI
2021 | Journal Article | IST-REx-ID: 15267 |
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 |
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 |
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.
[Published Version]
View
| Download Published Version (ext.)