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121 Publications

2021 | Conference Paper | IST-REx-ID: 10049 | OA
Klein, Karen, et al. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” 2021 IEEE Symposium on Security and Privacy , IEEE, 2021, pp. 268–84, doi:10.1109/sp40001.2021.00035.
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2021 | Conference Paper | IST-REx-ID: 10854 | OA
Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication Networks.” Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp. 71–72, doi:10.1145/3410220.3453923.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Journal Article | IST-REx-ID: 10855 | OA
Foerster, Klaus-Tycho, et al. “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, 2021, pp. 1–33, doi:10.1145/3447384.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Thesis | IST-REx-ID: 10429 | OA
Nadiradze, Giorgi. On Achieving Scalability through Relaxation. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10429.
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2021 | Conference Paper | IST-REx-ID: 10435 | OA
Nadiradze, Giorgi, et al. “Asynchronous Decentralized SGD with Quantized and Local Updates.” 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Journal Article | IST-REx-ID: 9541 | OA
Czumaj, Artur, et al. “Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space.” ACM Transactions on Algorithms, vol. 17, no. 2, 16, Association for Computing Machinery, 2021, doi:10.1145/3451992.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | WoS | arXiv
 
2021 | Conference Paper | IST-REx-ID: 9678 | OA
Brandt, Sebastian, et al. “Efficient Load-Balancing through Distributed Token Dropping.” Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2021, pp. 129–39, doi:10.1145/3409964.3461785.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2021 | Journal Article | IST-REx-ID: 8286 | OA
Alistarh, Dan-Adrian, et al. “Dynamic Averaging Load Balancing on Cycles.” Algorithmica, Springer Nature, 2021, doi:10.1007/s00453-021-00905-9.
[Published Version] View | Files available | DOI | WoS | arXiv
 
2021 | Journal Article | IST-REx-ID: 9571 | OA
Ramezani-Kebrya, Ali, et al. “NUQSGD: Provably Communication-Efficient Data-Parallel SGD via Nonuniform Quantization.” Journal of Machine Learning Research, vol. 22, no. 114, Journal of Machine Learning Research, 2021, p. 1−43.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Journal Article | IST-REx-ID: 7939 | OA
Censor-Hillel, Keren, et al. “Fast Approximate Shortest Paths in the Congested Clique.” Distributed Computing, vol. 34, Springer Nature, 2021, pp. 463–87, doi: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, Artur, et al. “Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC.” SIAM Journal on Computing, vol. 50, no. 5, Society for Industrial & Applied Mathematics, 2021, pp. 1603–26, doi:10.1137/20m1366502.
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2021 | Journal Article | IST-REx-ID: 15267 | OA
Czumaj, Artur, and Peter Davies. “Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks.” Journal of the ACM, vol. 68, no. 2, 13, Association for Computing Machinery, 2021, doi:10.1145/3446383.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 15263 | OA
Alimisis, Foivos, et al. “Momentum Improves Optimization on Riemannian Manifolds.” Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, vol. 130, ML Research Press, 2021, pp. 1351–59.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7272 | OA
Arbel-Raviv, Maya, et al. “Getting to the Root of Concurrent Binary Search Tree Performance.” Proceedings of the 2018 USENIX Annual Technical Conference, USENIX Association, 2020, pp. 295–306.
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2020 | Conference Paper | IST-REx-ID: 7605 | OA
Alistarh, Dan-Adrian, et al. “In Search of the Fastest Concurrent Union-Find Algorithm.” 23rd International Conference on Principles of Distributed Systems, vol. 153, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020, p. 15:1-15:16, doi:10.4230/LIPIcs.OPODIS.2019.15.
[Published Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 7803 | OA
Czumaj, Artur, et al. “Simple, Deterministic, Constant-Round Coloring in the Congested Clique.” Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2020, pp. 309–18, doi:10.1145/3382734.3405751.
[Submitted Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 8725 | OA
Aksenov, Vitaly, et al. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” 34th International Symposium on Distributed Computing, vol. 179, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020, p. 3:1-3:18, doi:10.4230/LIPIcs.DISC.2020.3.
[Published Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9632 | OA
Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression.” Advances in Neural Information Processing Systems, vol. 33, Curran Associates, 2020, pp. 18098–109.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9631 | OA
Aksenov, Vitaly, et al. “Scalable Belief Propagation via Relaxed Scheduling.” Advances in Neural Information Processing Systems, vol. 33, Curran Associates, 2020, pp. 22361–72.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9415 | OA
Kurtz, Mark, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” 37th International Conference on Machine Learning, ICML 2020, vol. 119, 2020, pp. 5533–43.
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