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121 Publications

2021 | 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 | 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 | 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 | 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 | Conference Paper | IST-REx-ID: 10853 | OA
A. Fedorov, N. Koval, and D.-A. Alistarh, “A scalable concurrent algorithm for dynamic connectivity,” in Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Virtual, Online, 2021, pp. 208–220.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | 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 | 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 | 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 | 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 | Conference Paper | IST-REx-ID: 9543 | OA
P. Davies, V. Gurunanthan, N. Moshrefi, S. Ashkboos, and D.-A. Alistarh, “New bounds for distributed mean estimation and variance reduction,” in 9th International Conference on Learning Representations, Virtual, 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 9620 | OA
D.-A. Alistarh and P. Davies, “Collecting coupons is faster with friends,” in Structural Information and Communication Complexity, Wrocław, Poland, 2021, vol. 12810, pp. 3–12.
[Preprint] View | Files available | DOI
 
2021 | Conference Paper | IST-REx-ID: 9823 | OA
D.-A. Alistarh, F. Ellen, and J. Rybicki, “Wait-free approximate agreement on graphs,” in Structural Information and Communication Complexity, Wrocław, Poland, 2021, vol. 12810, pp. 87–105.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 11458 | OA
E.-A. Peste, 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 | 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 | 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
 
2021 | Journal Article | IST-REx-ID: 9827 | OA
B. Chatterjee, I. Walulya, and P. Tsigas, “Concurrent linearizable nearest neighbour search in LockFree-kD-tree,” Theoretical Computer Science, vol. 886. Elsevier, pp. 27–48, 2021.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
2021 | Conference Paper | IST-REx-ID: 9951
D.-A. Alistarh, M. Töpfer, and P. Uznański, “Comparison dynamics in population protocols,” in Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, Virtual, Italy, 2021, pp. 55–65.
View | DOI | WoS
 
2021 | 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 | 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 | 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
 

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