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121 Publications
2021 | Conference Paper | IST-REx-ID: 10049 | 
Klein, Karen, Guillermo Pascual Perez, Michael Walter, Chethan Kamath Hosdurg, Margarita Capretto, Miguel Cueto Noval, Ilia Markov, Michelle X Yeo, Joel F Alwen, and Krzysztof Z Pietrzak. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” In 2021 IEEE Symposium on Security and Privacy , 268–84. IEEE, 2021. https://doi.org/10.1109/sp40001.2021.00035.
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2021 | Conference Paper | IST-REx-ID: 10854 |
Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan 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, 71–72. Association for Computing Machinery, 2021. https://doi.org/10.1145/3410220.3453923.
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| arXiv
2021 | Journal Article | IST-REx-ID: 10855 |
Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery, 2021. https://doi.org/10.1145/3447384.
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2021 | Thesis | IST-REx-ID: 10429 |
Nadiradze, Giorgi. “On Achieving Scalability through Relaxation.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10429.
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2021 | Conference Paper | IST-REx-ID: 10435 |
Nadiradze, Giorgi, Amirmojtaba Sabour, Peter Davies, Shigang Li, and Dan-Adrian Alistarh. “Asynchronous Decentralized SGD with Quantized and Local Updates.” In 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation, 2021.
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| arXiv
2021 | Journal Article | IST-REx-ID: 9541 |
Czumaj, Artur, Peter Davies, and Merav Parter. “Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space.” ACM Transactions on Algorithms. Association for Computing Machinery, 2021. https://doi.org/10.1145/3451992.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 9678 |
Brandt, Sebastian, Barbara Keller, Joel Rybicki, Jukka Suomela, and Jara Uitto. “Efficient Load-Balancing through Distributed Token Dropping.” In Annual ACM Symposium on Parallelism in Algorithms and Architectures, 129–39, 2021. https://doi.org/10.1145/3409964.3461785.
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| arXiv
2021 | Journal Article | IST-REx-ID: 8286 |
Alistarh, Dan-Adrian, Giorgi Nadiradze, and Amirmojtaba Sabour. “Dynamic Averaging Load Balancing on Cycles.” Algorithmica. Springer Nature, 2021. https://doi.org/10.1007/s00453-021-00905-9.
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| arXiv
2021 | Journal Article | IST-REx-ID: 9571 |
Ramezani-Kebrya, Ali, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan-Adrian Alistarh, and Daniel M. Roy. “NUQSGD: Provably Communication-Efficient Data-Parallel SGD via Nonuniform Quantization.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2021.
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| arXiv
2021 | Journal Article | IST-REx-ID: 7939 |
Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.” Distributed Computing. Springer Nature, 2021. https://doi.org/10.1007/s00446-020-00380-5.
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| arXiv
2021 | Journal Article | IST-REx-ID: 15271
Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC.” SIAM Journal on Computing. Society for Industrial & Applied Mathematics, 2021. https://doi.org/10.1137/20m1366502.
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2021 | Journal Article | IST-REx-ID: 15267 |
Czumaj, Artur, and Peter Davies. “Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks.” Journal of the ACM. Association for Computing Machinery, 2021. https://doi.org/10.1145/3446383.
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2021 | Conference Paper | IST-REx-ID: 15263 |
Alimisis, Foivos, Antonio Orvieto, Gary Becigneul, and Aurelien Lucchi. “Momentum Improves Optimization on Riemannian Manifolds.” In Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 130:1351–59. ML Research Press, 2021.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 7272 |
Arbel-Raviv, Maya, Trevor A Brown, and Adam Morrison. “Getting to the Root of Concurrent Binary Search Tree Performance.” In Proceedings of the 2018 USENIX Annual Technical Conference, 295–306. USENIX Association, 2020.
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2020 | Conference Paper | IST-REx-ID: 7605 |
Alistarh, Dan-Adrian, Alexander Fedorov, and Nikita Koval. “In Search of the Fastest Concurrent Union-Find Algorithm.” In 23rd International Conference on Principles of Distributed Systems, 153:15:1-15:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.OPODIS.2019.15.
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2020 | Conference Paper | IST-REx-ID: 7803 |
Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in the Congested Clique.” In Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing, 309–18. Association for Computing Machinery, 2020. https://doi.org/10.1145/3382734.3405751.
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2020 | Conference Paper | IST-REx-ID: 8725 |
Aksenov, Vitaly, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” In 34th International Symposium on Distributed Computing, 179:3:1-3:18. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.DISC.2020.3.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 9632 |
Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression.” In Advances in Neural Information Processing Systems, 33:18098–109. Curran Associates, 2020.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 9631 |
Aksenov, Vitaly, Dan-Adrian Alistarh, and Janne Korhonen. “Scalable Belief Propagation via Relaxed Scheduling.” In Advances in Neural Information Processing Systems, 33:22361–72. Curran Associates, 2020.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 9415 |
Kurtz, Mark, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” In 37th International Conference on Machine Learning, ICML 2020, 119:5533–43, 2020.
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