Communication-efficient distributed optimization with quantized preconditioners
F. Alimisis, P. Davies, D.-A. Alistarh, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 196–206.

Breaking (global) barriers in parallel stochastic optimization with wait-avoiding group averaging
S. Li, T.B.-N. Tal Ben-Nun, G. Nadiradze, S.D. Girolamo, N. Dryden, D.-A. Alistarh, T. Hoefler, IEEE Transactions on Parallel and Distributed Systems 32 (2021).

Concurrent linearizable nearest neighbour search in LockFree-kD-tree
B. Chatterjee, I. Walulya, P. Tsigas, Theoretical Computer Science 886 (2021) 27–48.

Comparison dynamics in population protocols
D.-A. Alistarh, M. Töpfer, P. Uznaski, in:, Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2021, pp. 55–65.

Improved deterministic (+1) coloring in low-space MPC
A. Czumaj, P. Davies, M. Parter, in:, Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2021, pp. 469–479.

Component stability in low-space massively parallel computation
A. Czumaj, P. Davies, M. Parter, in:, Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2021, pp. 481–491.

Elastic consistency: A practical consistency model for distributed stochastic gradient descent
G. Nadiradze, I. Markov, B. Chatterjee, V. Kungurtsev, D.-A. Alistarh, in:, Proceedings of the AAAI Conference on Artificial Intelligence, 2021, pp. 9037–9045.

Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement
K. Klein, G. Pascual Perez, M. Walter, C. Kamath Hosdurg, M. Capretto, M. Cueto Noval, I. Markov, M.X. Yeo, J.F. Alwen, K.Z. Pietrzak, in:, 2021 IEEE Symposium on Security and Privacy , IEEE, 2021, pp. 268–284.

Input-dynamic distributed algorithms for communication networks
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, in:, Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp. 71–72.

Input-dynamic distributed algorithms for communication networks
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, Proceedings of the ACM on Measurement and Analysis of Computing Systems 5 (2021) 1–33.

On achieving scalability through relaxation
G. Nadiradze, On Achieving Scalability through Relaxation, Institute of Science and Technology Austria, 2021.

Asynchronous decentralized SGD with quantized and local updates
G. Nadiradze, A. Sabour, P. Davies, S. Li, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021.

Graph sparsification for derandomizing massively parallel computation with low space
A. Czumaj, P. Davies, M. Parter, ACM Transactions on Algorithms 17 (2021).

Efficient load-balancing through distributed token dropping
S. Brandt, B. Keller, J. Rybicki, J. Suomela, J. Uitto, in:, Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2021, pp. 129–139.

NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization
A. Ramezani-Kebrya, F. Faghri, I. Markov, V. Aksenov, D.-A. Alistarh, D.M. Roy, Journal of Machine Learning Research 22 (2021) 143.

Fast approximate shortest paths in the congested clique
K. Censor-Hillel, M. Dory, J. Korhonen, D. Leitersdorf, Distributed Computing 34 (2021) 463–487.

Simple, deterministic, constant-round coloring in congested clique and MPC
A. Czumaj, P. Davies, M. Parter, SIAM Journal on Computing 50 (2021) 1603–1626.

Exploiting spontaneous transmissions for broadcasting and leader election in radio networks
A. Czumaj, P. Davies, Journal of the ACM 68 (2021).

Momentum improves optimization on Riemannian manifolds
F. Alimisis, A. Orvieto, G. Becigneul, A. Lucchi, in:, Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2021, pp. 1351–1359.

Getting to the root of concurrent binary search tree performance
M. Arbel-Raviv, T.A. Brown, A. Morrison, in:, Proceedings of the 2018 USENIX Annual Technical Conference, USENIX Association, 2020, pp. 295–306.