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Alistarh D-A, Ellen F, Rybicki J. Wait-free approximate agreement on graphs. In: Structural Information and Communication Complexity. Vol 12810. Springer Nature; 2021:87-105. doi:10.1007/978-3-030-79527-6_6
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arXiv: 2103.08949

Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In: 35th Conference on Neural Information Processing Systems. Vol 34. Curran Associates; 2021:8557-8570.
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arXiv: 2106.12379

Alimisis F, Davies P, Alistarh D-A. Communication-efficient distributed optimization with quantized preconditioners. In: Proceedings of the 38th International Conference on Machine Learning. Vol 139. ML Research Press; 2021:196-206.
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Li S, Tal Ben-Nun TB-N, Nadiradze G, et al. Breaking (global) barriers in parallel stochastic optimization with wait-avoiding group averaging. IEEE Transactions on Parallel and Distributed Systems. 2021;32(7). doi:10.1109/TPDS.2020.3040606
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Chatterjee B, Walulya I, Tsigas P. Concurrent linearizable nearest neighbour search in LockFree-kD-tree. Theoretical Computer Science. 2021;886:27-48. doi:10.1016/j.tcs.2021.06.041
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Alistarh D-A, Töpfer M, Uznaski P. Comparison dynamics in population protocols. In: Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2021:55-65. doi:10.1145/3465084.3467915
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Czumaj A, Davies P, Parter M. Improved deterministic (+1) coloring in low-space MPC. In: Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2021:469–479. doi:10.1145/3465084.3467937
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Czumaj A, Davies P, Parter M. Component stability in low-space massively parallel computation. In: Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2021:481–491. doi:10.1145/3465084.3467903
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arXiv: 2106.01880

Nadiradze G, Markov I, Chatterjee B, Kungurtsev V, Alistarh D-A. Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. ; 2021:9037-9045.
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Klein K, Pascual Perez G, Walter M, et al. Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In: 2021 IEEE Symposium on Security and Privacy . IEEE; 2021:268-284. doi:10.1109/sp40001.2021.00035
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Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. In: Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery; 2021:71-72. doi:10.1145/3410220.3453923
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Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 2021;5(1):1-33. doi:10.1145/3447384
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Nadiradze G. On achieving scalability through relaxation. 2021. doi:10.15479/at:ista:10429
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Nadiradze G, Sabour A, Davies P, Li S, Alistarh D-A. 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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Czumaj A, Davies P, Parter M. Graph sparsification for derandomizing massively parallel computation with low space. ACM Transactions on Algorithms. 2021;17(2). doi:10.1145/3451992
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Brandt S, Keller B, Rybicki J, Suomela J, Uitto J. Efficient load-balancing through distributed token dropping. In: Annual ACM Symposium on Parallelism in Algorithms and Architectures. ; 2021:129-139. doi:10.1145/3409964.3461785
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Alistarh D-A, Nadiradze G, Sabour A. Dynamic averaging load balancing on cycles. Algorithmica. 2021. doi:10.1007/s00453-021-00905-9
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Ramezani-Kebrya A, Faghri F, Markov I, Aksenov V, Alistarh D-A, Roy DM. NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization. Journal of Machine Learning Research. 2021;22(114):143.
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Censor-Hillel K, Dory M, Korhonen J, Leitersdorf D. Fast approximate shortest paths in the congested clique. Distributed Computing. 2021;34:463-487. doi:10.1007/s00446-020-00380-5
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arXiv: 1903.05956