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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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Czumaj, A., Davies, P., &; Parter, M. (2021). Improved deterministic (+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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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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Klein, K., Pascual Perez, G., Walter, M., Kamath Hosdurg, C., Capretto, M., Cueto Noval, M.,https://doi.org/10.1109/sp40001.2021.00035__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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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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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).https://doi.org/10.1145/3409964.3461785__Virtual Event, United States.https://doi.org/10.1145/3409964.3461785 
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