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152 Publications

2021 | Published | Journal Article | IST-REx-ID: 7939 | OA
K. Censor-Hillel, M. Dory, J. Korhonen, and D. Leitersdorf, “Fast approximate shortest paths in the congested clique,” Distributed Computing, vol. 34. Springer Nature, pp. 463–487, 2021.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 9933 | OA
A. Czumaj, P. Davies, and M. Parter, “Component stability in low-space massively parallel computation,” in Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Virtual, Italy, 2021, pp. 481–491.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 9935 | OA
A. Czumaj, P. Davies, and M. Parter, “Improved deterministic (Δ+1) coloring in low-space MPC,” in Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Virtual, Italy, 2021, pp. 469–479.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
2021 | Published | Journal Article | IST-REx-ID: 9541 | OA
A. Czumaj, P. Davies, and M. Parter, “Graph sparsification for derandomizing massively parallel computation with low space,” ACM Transactions on Algorithms, vol. 17, no. 2. Association for Computing Machinery, 2021.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11436 | OA
V. Kungurtsev, M. Egan, B. Chatterjee, and D.-A. Alistarh, “Asynchronous optimization methods for efficient training of deep neural networks with guarantees,” in 35th AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Online, 2021, vol. 35, no. 9B, pp. 8209–8216.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10435 | OA
G. Nadiradze, A. Sabour, P. Davies, S. Li, and D.-A. Alistarh, “Asynchronous decentralized SGD with quantized and local updates,” in 35th Conference on Neural Information Processing Systems, Sydney, Australia, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11452 | OA
F. Alimisis, P. Davies, B. Vandereycken, and D.-A. Alistarh, “Distributed principal component analysis with limited communication,” in Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 4, pp. 2823–2834.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10432 | OA
G. Nadiradze, I. Markov, B. Chatterjee, V. Kungurtsev, and D.-A. Alistarh, “Elastic consistency: A practical consistency model for distributed stochastic gradient descent,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 10, pp. 9037–9045.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10049 | OA
K. Klein et al., “Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement,” in 2021 IEEE Symposium on Security and Privacy , San Francisco, CA, United States, 2021, pp. 268–284.
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2021 | Published | Conference Paper | IST-REx-ID: 11458 | OA
A. Krumes, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating Compressed/DeCompressed training of deep neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 8557–8570.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11463 | OA
E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free approximations of second-order information,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 11464 | OA
D.-A. Alistarh and J. Korhonen, “Towards tight communication lower bounds for distributed optimisation,” in 35th Conference on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34, pp. 7254–7266.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 15271
A. Czumaj, P. Davies, and M. Parter, “Simple, deterministic, constant-round coloring in congested clique and MPC,” SIAM Journal on Computing, vol. 50, no. 5. Society for Industrial and Applied Mathematics, pp. 1603–1626, 2021.
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2021 | Published | Conference Paper | IST-REx-ID: 10219 | OA
J. Korhonen, A. Paz, J. Rybicki, S. Schmid, and J. Suomela, “Brief announcement: Sinkless orientation is hard also in the supported LOCAL model,” in 35th International Symposium on Distributed Computing, Freiburg, Germany, 2021, vol. 209.
[Published Version] View | Files available | DOI | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10217 | OA
D.-A. Alistarh, R. Gelashvili, and G. Nadiradze, “Lower bounds for shared-memory leader election under bounded write contention,” in 35th International Symposium on Distributed Computing, Freiburg, Germany, 2021, vol. 209.
[Published Version] View | Files available | DOI
 
2021 | Published | Conference Paper | IST-REx-ID: 10216 | OA
B. Chatterjee, S. Peri, and M. Sa, “Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds,” in 35th International Symposium on Distributed Computing, Freiburg, Germany, 2021, vol. 209.
[Published Version] View | Files available | DOI | arXiv
 
2021 | Published | Thesis | IST-REx-ID: 10429 | OA
G. Nadiradze, “On achieving scalability through relaxation,” Institute of Science and Technology Austria, 2021.
[Published Version] View | Files available | DOI
 
2021 | Published | Journal Article | IST-REx-ID: 10180 | OA
T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, and A. Krumes, “Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks,” Journal of Machine Learning Research, vol. 22, no. 241. ML Research Press, pp. 1–124, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 13147 | OA
F. Alimisis, P. Davies, and D.-A. Alistarh, “Communication-efficient distributed optimization with quantized preconditioners,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 196–206.
[Published Version] View | Files available | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 8723 | OA
S. Li et al., “Breaking (global) barriers in parallel stochastic optimization with wait-avoiding group averaging,” IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 7. IEEE, 2021.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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