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121 Publications


2022 | Journal Article | IST-REx-ID: 11420 | OA
Shevchenko, A., Kungurtsev, V., & Mondelli, M. (2022). Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. Journal of Machine Learning Research.
[Published Version] View | Files available | arXiv
 

2022 | Conference Paper | IST-REx-ID: 12182 | OA
Pacut, M., Parham, M., Rybicki, J., Schmid, S., Suomela, J., & Tereshchenko, A. (2022). Brief announcement: Temporal locality in online algorithms. In 36th International Symposium on Distributed Computing (Vol. 246). Augusta, GA, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2022.52
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2022 | Conference Paper | IST-REx-ID: 12780 | OA
Markov, I., Ramezanikebrya, H., & Alistarh, D.-A. (2022). CGX: Adaptive system support for communication-efficient deep learning. In Proceedings of the 23rd ACM/IFIP International Middleware Conference (pp. 241–254). Quebec, QC, Canada: Association for Computing Machinery. https://doi.org/10.1145/3528535.3565248
[Published Version] View | Files available | DOI | arXiv
 

2022 | Conference Paper | IST-REx-ID: 11844 | OA
Alistarh, D.-A., Rybicki, J., & Voitovych, S. (2022). Near-optimal leader election in population protocols on graphs. In Proceedings of the Annual ACM Symposium on Principles of Distributed Computing (pp. 246–256). Salerno, Italy: Association for Computing Machinery. https://doi.org/10.1145/3519270.3538435
[Published Version] View | Files available | DOI | arXiv
 

2022 | Conference Paper | IST-REx-ID: 11181 | OA
Brown, T. A., Sigouin, W., & Alistarh, D.-A. (2022). PathCAS: An efficient middle ground for concurrent search data structures. In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (pp. 385–399). Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/3503221.3508410
[Published Version] View | Files available | DOI | WoS
 

2022 | Conference Paper | IST-REx-ID: 11180 | OA
Postnikova, A., Koval, N., Nadiradze, G., & Alistarh, D.-A. (2022). 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 (pp. 353–367). Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/3503221.3508432
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2022 | Research Data Reference | IST-REx-ID: 13076 | OA
Postnikova, A., Koval, N., Nadiradze, G., & Alistarh, D.-A. (2022). Multi-queues can be state-of-the-art priority schedulers. Zenodo. https://doi.org/10.5281/ZENODO.5733408
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2022 | Conference Paper | IST-REx-ID: 11707 | OA
Balliu, A., Hirvonen, J., Melnyk, D., Olivetti, D., Rybicki, J., & Suomela, J. (2022). Local mending. In M. Parter (Ed.), International Colloquium on Structural Information and Communication Complexity (Vol. 13298, pp. 1–20). Paderborn, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-09993-9_1
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2022 | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova, E. B., Peste, E.-A., Kurtz, M., & Alistarh, D.-A. (2022). How well do sparse ImageNet models transfer? In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 12256–12266). New Orleans, LA, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/cvpr52688.2022.01195
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2021 | Journal Article | IST-REx-ID: 10180 | OA
Hoefler, T., Alistarh, D.-A., Ben-Nun, T., Dryden, N., & Peste, E.-A. (2021). Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks. Journal of Machine Learning Research. Journal of Machine Learning Research.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10218 | OA
Alistarh, D.-A., Gelashvili, R., & Rybicki, J. (2021). Brief announcement: Fast graphical population protocols. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.43
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10217 | OA
Alistarh, D.-A., Gelashvili, R., & Nadiradze, G. (2021). Lower bounds for shared-memory leader election under bounded write contention. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.4
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2021 | Conference Paper | IST-REx-ID: 10216 | OA
Chatterjee, B., Peri, S., & Sa, M. (2021). Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.52
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10219 | OA
Korhonen, J., Paz, A., Rybicki, J., Schmid, S., & Suomela, J. (2021). Brief announcement: Sinkless orientation is hard also in the supported LOCAL model. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.58
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10853 | OA
Fedorov, A., Koval, N., & Alistarh, D.-A. (2021). A scalable concurrent algorithm for dynamic connectivity. In Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures (pp. 208–220). Virtual, Online: Association for Computing Machinery. https://doi.org/10.1145/3409964.3461810
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2021 | Conference Paper | IST-REx-ID: 11436 | OA
Kungurtsev, V., Egan, M., Chatterjee, B., & Alistarh, D.-A. (2021). Asynchronous optimization methods for efficient training of deep neural networks with guarantees. In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (Vol. 35, pp. 8209–8216). Virtual, Online: AAAI Press.
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2021 | Conference Paper | IST-REx-ID: 11452 | OA
Alimisis, F., Davies, P., Vandereycken, B., & Alistarh, D.-A. (2021). Distributed principal component analysis with limited communication. In Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems (Vol. 4, pp. 2823–2834). Virtual, Online: Neural Information Processing Systems Foundation.
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2021 | Conference Paper | IST-REx-ID: 11463 | OA
Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free approximations of second-order information. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Curran Associates.
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2021 | Conference Paper | IST-REx-ID: 11464 | OA
Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower bounds for distributed optimisation. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Curran Associates.
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2021 | Conference Paper | IST-REx-ID: 9543 | OA
Davies, P., Gurunanthan, V., Moshrefi, N., Ashkboos, S., & Alistarh, D.-A. (2021). New bounds for distributed mean estimation and variance reduction. In 9th International Conference on Learning Representations. Virtual.
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2021 | Conference Paper | IST-REx-ID: 9620 | OA
Alistarh, D.-A., & Davies, P. (2021). Collecting coupons is faster with friends. In Structural Information and Communication Complexity (Vol. 12810, pp. 3–12). Wrocław, Poland: Springer Nature. https://doi.org/10.1007/978-3-030-79527-6_1
[Preprint] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 9823 | OA
Alistarh, D.-A., Ellen, F., & Rybicki, J. (2021). Wait-free approximate agreement on graphs. In Structural Information and Communication Complexity (Vol. 12810, pp. 87–105). Wrocław, Poland: Springer Nature. https://doi.org/10.1007/978-3-030-79527-6_6
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2021 | Conference Paper | IST-REx-ID: 11458 | OA
Peste, E.-A., Iofinova, E. B., Vladu, A., & Alistarh, D.-A. (2021). AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 8557–8570). Virtual, Online: Curran Associates.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 13147 | OA
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 | OA
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
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2021 | Journal Article | IST-REx-ID: 9827 | OA
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
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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
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2021 | Conference Paper | IST-REx-ID: 9935 | OA
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
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2021 | Conference Paper | IST-REx-ID: 9933 | OA
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
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2021 | Conference Paper | IST-REx-ID: 10432 | OA
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.
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2021 | Conference Paper | IST-REx-ID: 10049 | OA
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
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2021 | Conference Paper | IST-REx-ID: 10854 | OA
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
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2021 | Journal Article | IST-REx-ID: 10855 | OA
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
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2021 | Thesis | IST-REx-ID: 10429 | OA
Nadiradze, G. (2021). On achieving scalability through relaxation. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10429
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2021 | Conference Paper | IST-REx-ID: 10435 | OA
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.
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2021 | Journal Article | IST-REx-ID: 9541 | OA
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
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2021 | Conference Paper | IST-REx-ID: 9678 | OA
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
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2021 | Journal Article | IST-REx-ID: 8286 | OA
Alistarh, D.-A., Nadiradze, G., & Sabour, A. (2021). Dynamic averaging load balancing on cycles. Algorithmica. Virtual, Online; Germany: Springer Nature. https://doi.org/10.1007/s00453-021-00905-9
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2021 | Journal Article | IST-REx-ID: 9571 | OA
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.
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2021 | Journal Article | IST-REx-ID: 7939 | OA
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
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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
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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.
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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.
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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.
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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.
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