Harnessing epoch-based reclamation for efficient range queries
M. Arbel Raviv, T.A. Brown, in:, ACM, 2018, pp. 14–27.
LibreCat: https://research-explorer.ista.ac.at/record/397
DOI: 10.1145/3178487.3178489
WoS: 000446161100002

Model of bacterial toxin-dependent pathogenesis explains infective dose
J. Rybicki, E. Kisdi, J. Anttila, PNAS 115 (2018) 10690–10695.
LibreCat: https://research-explorer.ista.ac.at/record/43
DOI: 10.1073/pnas.1721061115
WoS: 000447491300057

Near-optimal self-stabilising counting and firing squads
C. Lenzen, J. Rybicki, Distributed Computing (2018).
LibreCat: https://research-explorer.ista.ac.at/record/76
DOI: 10.1007/s00446-018-0342-6
WoS: 000475627800005

Snapshot based synchronization: A fast replacement for Hand-over-Hand locking
E. Gilad, T.A. Brown, M. Oskin, Y. Etsion, in:, Springer, 2018, pp. 465–479.
LibreCat: https://research-explorer.ista.ac.at/record/85
DOI: 10.1007/978-3-319-96983-1_33
WoS: 000851042300031

The convergence of stochastic gradient descent in asynchronous shared memory
D.-A. Alistarh, C. De Sa, N.H. Konstantinov, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 169–178.
LibreCat: https://research-explorer.ista.ac.at/record/5962
DOI: 10.1145/3212734.3212763
WoS: 000458186900022
arXiv: 1803.08841

A brief tutorial on distributed and concurrent machine learning
D.-A. Alistarh, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 487–488.
LibreCat: https://research-explorer.ista.ac.at/record/5961
DOI: 10.1145/3212734.3212798
WoS: 000458186900063

Relaxed schedulers can efficiently parallelize iterative algorithms
D.-A. Alistarh, T.A. Brown, J. Kopinsky, G. Nadiradze, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 377–386.
LibreCat: https://research-explorer.ista.ac.at/record/5963
DOI: 10.1145/3212734.3212756
WoS: 000458186900048
arXiv: 1808.04155

Distributionally linearizable data structures
D.-A. Alistarh, T.A. Brown, J. Kopinsky, J.Z. Li, G. Nadiradze, in:, Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, ACM Press, 2018, pp. 133–142.
LibreCat: https://research-explorer.ista.ac.at/record/5965
DOI: 10.1145/3210377.3210411
WoS: 000545269600016
arXiv: 1804.01018

The transactional conflict problem
D.-A. Alistarh, S.K. Haider, R. Kübler, G. Nadiradze, in:, Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, ACM Press, 2018, pp. 383–392.
LibreCat: https://research-explorer.ista.ac.at/record/5966
DOI: 10.1145/3210377.3210406
WoS: 000545269600046
arXiv: 1804.00947

Brief Announcement: Performance prediction for coarse-grained locking
V. Aksenov, D.-A. Alistarh, P. Kuznetsov, in:, Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, ACM Press, 2018, pp. 411–413.
LibreCat: https://research-explorer.ista.ac.at/record/5964
DOI: 10.1145/3212734.3212785
WoS: 000458186900052

Fast quantized arithmetic on : Trading compute for data movement
A. Stojanov, T.M. Smith, D.-A. Alistarh, M. Puschel, in:, 2018 IEEE International Workshop on Signal Processing Systems, IEEE, 2018.
LibreCat: https://research-explorer.ista.ac.at/record/6031
DOI: 10.1109/SiPS.2018.8598402
WoS: 000465106800060

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.
LibreCat: https://research-explorer.ista.ac.at/record/7123
DOI: 10.1137/1.9781611975031.144
WoS: 000483921200145
arXiv: 1704.04947

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.
LibreCat: https://research-explorer.ista.ac.at/record/6558
WoS: 000461823304061
arXiv: 1803.08917

The convergence of sparsified gradient methods
D.-A. Alistarh, T. Hoefler, M. Johansson, N.H. Konstantinov, S. Khirirat, C. Renggli, in:, Advances in Neural Information Processing Systems 31, Neural Information Processing Systems Foundation, 2018, pp. 5973–5983.
LibreCat: https://research-explorer.ista.ac.at/record/6589
WoS: 000461852000047
arXiv: 1809.10505

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.
LibreCat: https://research-explorer.ista.ac.at/record/487
DOI: 10.1145/3143361.3143367

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.
LibreCat: https://research-explorer.ista.ac.at/record/791
DOI: 10.1145/3087801.3087810
WoS: 000462995000035

QSGD: Communication-efficient SGD via gradient quantization and encoding
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, M. Vojnovi, in:, Neural Information Processing Systems Foundation, 2017, pp. 1710–1721.
LibreCat: https://research-explorer.ista.ac.at/record/431
arXiv: 1610.02132

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.
LibreCat: https://research-explorer.ista.ac.at/record/432