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164 Publications
2021 |
Published |
Conference Paper |
IST-REx-ID: 10853 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10854 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 10855 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 11436 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10049 |
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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| WoS
2021 |
Published |
Journal Article |
IST-REx-ID: 10180 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10216 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10217 |
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.
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2021 |
Published |
Conference Paper |
IST-REx-ID: 10218 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10219 |
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.
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| arXiv
2021 |
Published |
Thesis | PhD |
IST-REx-ID: 10429 |
G. Nadiradze, “On achieving scalability through relaxation,” Institute of Science and Technology Austria, 2021.
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2021 |
Published |
Conference Paper |
IST-REx-ID: 10432 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 10435 |
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.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 7939 |
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.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 8723 |
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.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 9541 |
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.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 9543 |
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.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 9571 |
A. Ramezani-Kebrya, F. Faghri, I. Markov, V. Aksenov, D.-A. Alistarh, and D. M. Roy, “NUQSGD: Provably communication-efficient data-parallel SGD via nonuniform quantization,” Journal of Machine Learning Research, vol. 22, no. 114. Journal of Machine Learning Research, p. 1−43, 2021.
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| arXiv
2021 |
Published |
Conference Paper |
IST-REx-ID: 9620 |
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]
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2021 |
Published |
Conference Paper |
IST-REx-ID: 9678 |
S. Brandt, B. Keller, J. Rybicki, J. Suomela, and J. Uitto, “Efficient load-balancing through distributed token dropping,” in Annual ACM Symposium on Parallelism in Algorithms and Architectures, Virtual Event, United States, 2021, pp. 129–139.
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| arXiv