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170 Publications


2018 | Published | Conference Paper | IST-REx-ID: 6558 | OA
Byzantine stochastic gradient descent
D.-A. Alistarh, Z. Allen-Zhu, J. Li, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018, pp. 4613–4623.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 7116 | OA
Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study
D. Grubic, L. Tam, D.-A. Alistarh, C. Zhang, in:, Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–156.
[Published Version] View | Files available | DOI
 

2018 | Published | Conference Paper | IST-REx-ID: 7123 | OA
Space-optimal majority in population protocols
D.-A. Alistarh, J. Aspnes, R. Gelashvili, in:, Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, ACM, 2018, pp. 2221–2239.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Published | Conference Paper | IST-REx-ID: 397
Harnessing epoch-based reclamation for efficient range queries
M. Arbel Raviv, T.A. Brown, in:, ACM, 2018, pp. 14–27.
View | DOI | WoS
 

2018 | Published | Journal Article | IST-REx-ID: 43 | OA
Model of bacterial toxin-dependent pathogenesis explains infective dose
J. Rybicki, E. Kisdi, J. Anttila, Proceedings of the National Academy of Sciences of the United States of America 115 (2018) 10690–10695.
[Submitted Version] View | Files available | DOI | WoS
 

2018 | Published | Conference Paper | IST-REx-ID: 6589 | OA
The convergence of sparsified gradient methods
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, 32nd Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018, pp. 5973–5983.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 

2017 | Published | Conference Paper | IST-REx-ID: 487
Towards unlicensed cellular networks in TV white spaces
G. Baig, B. Radunovic, D.-A. Alistarh, M. Balkwill, T. Karagiannis, L. Qiu, in:, Proceedings of the 2017 13th International Conference on Emerging Networking EXperiments and Technologies, ACM, 2017, pp. 2–14.
View | DOI | WoS
 

2017 | Published | Conference Paper | IST-REx-ID: 791 | OA
The power of choice in priority scheduling
D.-A. Alistarh, J. Kopinsky, J. Li, G. Nadiradze, in:, Proceedings of the ACM Symposium on Principles of Distributed Computing, ACM, 2017, pp. 283–292.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 

2017 | Published | Conference Paper | IST-REx-ID: 431 | OA
QSGD: Communication-efficient SGD via gradient quantization and encoding
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, M. Vojnović, in:, Neural Information Processing Systems Foundation, 2017, pp. 1710–1721.
[Submitted Version] View | Download Submitted Version (ext.) | WoS | arXiv
 

2017 | Published | Conference Paper | IST-REx-ID: 432 | OA
ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning
H. Zhang, J. Li, K. Kara, D.-A. Alistarh, J. Liu, C. Zhang, in:, Proceedings of Machine Learning Research, ML Research Press, 2017, pp. 4035–4043.
[Submitted Version] View | Files available | WoS
 

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