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Dan Alistarh

Jiale Chen

Vage Egiazarian

Eldar Kurtic

Ionut-Vlad Modoranu

Mahdi Nikdan

Andrei Panferov

Sergei Pankratov

Ileana Rugina

Erik Schultheis

Soroush Tabesh

Alexandra Volkova

Filipp Zmushko

Sharareh Alipour

Vitalii Aksenov

Trevor Brown

Bapi Chatterjee

Elvir Crncevic

Peter Davies

Alexander Fedorov

Elias Frantar

Janne Korhonen

Roberto Lopez Castro

Ilia Markov

Giorgi Nadiradze

Alexandra Krumes

Joel Rybicki

Mher Safaryan

Sidak Singh

Martin Töpfer

Sokolova, Mariia



170 Publications

2021 | Published | Journal Article | IST-REx-ID: 10855 | OA
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | 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: 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 | 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 | Conference Paper | IST-REx-ID: 15263 | OA
F. Alimisis, A. Orvieto, G. Becigneul, and A. Lucchi, “Momentum improves optimization on Riemannian manifolds,” in Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, San Diego, CA, United States; Virtual, 2021, vol. 130, pp. 1351–1359.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 15267 | OA
A. Czumaj and P. Davies, “Exploiting spontaneous transmissions for broadcasting and leader election in radio networks,” Journal of the ACM, vol. 68, no. 2. Association for Computing Machinery, 2021.
[Preprint] View | DOI | Download Preprint (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.
View | DOI | WoS
 
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.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS
 
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: 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 | 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: 10218 | OA
D.-A. Alistarh, R. Gelashvili, and J. Rybicki, “Brief announcement: Fast graphical population protocols,” 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: 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 | Thesis | PhD | 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 | 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: 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 | 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 | 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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