Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
121 Publications
2019 | Conference Paper | IST-REx-ID: 7201 | 
C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, and T. Hoefler, “SparCML: High-performance sparse communication for machine learning,” in International Conference for High Performance Computing, Networking, Storage and Analysis, SC, Denver, CO, Unites States, 2019.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Journal Article | IST-REx-ID: 7214 |
S. Aganezov, I. Zban, V. Aksenov, N. Alexeev, and M. C. Schatz, “Recovering rearranged cancer chromosomes from karyotype graphs,” BMC Bioinformatics, vol. 20. BMC, 2019.
[Published Version]
View
| Files available
| DOI
| WoS
2019 | Conference Paper | IST-REx-ID: 7437 |
C. Yu et al., “Distributed learning over unreliable networks,” in 36th International Conference on Machine Learning, ICML 2019, Long Beach, CA, United States, 2019, vol. 2019–June, pp. 12481–12512.
[Preprint]
View
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6673 |
D.-A. Alistarh, G. Nadiradze, and N. Koval, “Efficiency guarantees for parallel incremental algorithms under relaxed schedulers,” in 31st ACM Symposium on Parallelism in Algorithms and Architectures, Phoenix, AZ, United States, 2019, pp. 145–154.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 7542 |
C. Wendler, D.-A. Alistarh, and M. Püschel, “Powerset convolutional neural networks,” presented at the NIPS: Conference on Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 927–938.
[Published Version]
View
| Download Published Version (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6935 |
K.-T. Foerster, J. Korhonen, J. Rybicki, and S. Schmid, “Does preprocessing help under congestion?,” in Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, Toronto, ON, Canada, 2019, pp. 259–261.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6676 |
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, and L. Zhu, “Why extension-based proofs fail,” in Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, Phoenix, AZ, United States, 2019, pp. 986–996.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6933 |
K. Censor-Hillel, M. Dory, J. Korhonen, and D. Leitersdorf, “Fast approximate shortest paths in the congested clique,” in Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, Toronto, ON, Canada, 2019, pp. 74–83.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Journal Article | IST-REx-ID: 536 |
D.-A. Alistarh, J. Aspnes, V. King, and J. Saia, “Communication-efficient randomized consensus,” Distributed Computing, vol. 31, no. 6. Springer, pp. 489–501, 2018.
[Published Version]
View
| Files available
| DOI
2018 | Conference Paper | IST-REx-ID: 7116 |
D. Grubic, L. Tam, D.-A. Alistarh, and C. Zhang, “Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study,” in Proceedings of the 21st International Conference on Extending Database Technology, Vienna, Austria, 2018, pp. 145–156.
[Published Version]
View
| Files available
| DOI
2018 | Journal Article | IST-REx-ID: 6001
D.-A. Alistarh, W. Leiserson, A. Matveev, and N. Shavit, “ThreadScan: Automatic and scalable memory reclamation,” ACM Transactions on Parallel Computing, vol. 4, no. 4. Association for Computing Machinery, 2018.
View
| Files available
| DOI
2018 | Conference Paper | IST-REx-ID: 7812 |
A. Polino, R. Pascanu, and D.-A. Alistarh, “Model compression via distillation and quantization,” in 6th International Conference on Learning Representations, Vancouver, Canada, 2018.
[Published Version]
View
| Files available
| arXiv
2018 | Journal Article | IST-REx-ID: 43 |
J. Rybicki, E. Kisdi, and J. Anttila, “Model of bacterial toxin-dependent pathogenesis explains infective dose,” PNAS, vol. 115, no. 42. National Academy of Sciences, pp. 10690–10695, 2018.
[Submitted Version]
View
| Files available
| DOI
| WoS
2018 | Journal Article | IST-REx-ID: 76 |
C. Lenzen and J. Rybicki, “Near-optimal self-stabilising counting and firing squads,” Distributed Computing. Springer, 2018.
[Published Version]
View
| Files available
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 85 |
E. Gilad, T. A. Brown, M. Oskin, and Y. Etsion, “Snapshot based synchronization: A fast replacement for Hand-over-Hand locking,” presented at the Euro-Par: European Conference on Parallel Processing, Turin, Italy, 2018, vol. 11014, pp. 465–479.
[Preprint]
View
| Files available
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 5962 |
D.-A. Alistarh, C. De Sa, and N. H. Konstantinov, “The convergence of stochastic gradient descent in asynchronous shared memory,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 169–178.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 5963 |
D.-A. Alistarh, T. A. Brown, J. Kopinsky, and G. Nadiradze, “Relaxed schedulers can efficiently parallelize iterative algorithms,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 377–386.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 5965 |
D.-A. Alistarh, T. A. Brown, J. Kopinsky, J. Z. Li, and G. Nadiradze, “Distributionally linearizable data structures,” in Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, Vienna, Austria, 2018, pp. 133–142.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 5966 |
D.-A. Alistarh, S. K. Haider, R. Kübler, and G. Nadiradze, “The transactional conflict problem,” in Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, Vienna, Austria, 2018, pp. 383–392.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 5964 |
V. Aksenov, D.-A. Alistarh, and P. Kuznetsov, “Brief Announcement: Performance prediction for coarse-grained locking,” in Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, Egham, United Kingdom, 2018, pp. 411–413.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2018 | Conference Paper | IST-REx-ID: 6031
A. Stojanov, T. M. Smith, D.-A. Alistarh, and M. Puschel, “Fast quantized arithmetic on x86: Trading compute for data movement,” in 2018 IEEE International Workshop on Signal Processing Systems, Cape Town, South Africa, 2018, vol. 2018–October.
View
| DOI
| WoS
2018 | Conference Paper | IST-REx-ID: 7123 |
D.-A. Alistarh, J. Aspnes, and R. Gelashvili, “Space-optimal majority in population protocols,” in Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, LA, United States, 2018, pp. 2221–2239.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 6558 |
D.-A. Alistarh, Z. Allen-Zhu, and J. Li, “Byzantine stochastic gradient descent,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2018, vol. 2018, pp. 4613–4623.
[Published Version]
View
| Download Published Version (ext.)
| WoS
| arXiv
2018 | Conference Paper | IST-REx-ID: 6589 |
D.-A. Alistarh, T. Hoefler, M. Johansson, N. H. Konstantinov, S. Khirirat, and C. Renggli, “The convergence of sparsified gradient methods,” in Advances in Neural Information Processing Systems 31, Montreal, Canada, 2018, vol. Volume 2018, pp. 5973–5983.
[Preprint]
View
| Download Preprint (ext.)
| WoS
| arXiv
2017 | Conference Paper | IST-REx-ID: 487
G. Baig, B. Radunovic, D.-A. Alistarh, M. Balkwill, T. Karagiannis, and L. Qiu, “Towards unlicensed cellular networks in TV white spaces,” in Proceedings of the 2017 13th International Conference on emerging Networking EXperiments and Technologies, Incheon, South Korea, 2017, pp. 2–14.
View
| DOI
2017 | Conference Paper | IST-REx-ID: 791 |
D.-A. Alistarh, J. Kopinsky, J. Li, and G. Nadiradze, “The power of choice in priority scheduling,” in Proceedings of the ACM Symposium on Principles of Distributed Computing, Washington, WA, USA, 2017, vol. Part F129314, pp. 283–292.
[Submitted Version]
View
| DOI
| Download Submitted Version (ext.)
| WoS
2017 | Conference Paper | IST-REx-ID: 431 |
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, and M. Vojnović, “QSGD: Communication-efficient SGD via gradient quantization and encoding,” presented at the NIPS: Neural Information Processing System, Long Beach, CA, United States, 2017, vol. 2017, pp. 1710–1721.
[Submitted Version]
View
| Download Submitted Version (ext.)
| arXiv
2017 | Conference Paper | IST-REx-ID: 432 |
H. Zhang, J. Li, K. Kara, D.-A. Alistarh, J. Liu, and C. Zhang, “ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning,” in Proceedings of Machine Learning Research, Sydney, Australia, 2017, vol. 70, pp. 4035–4043.
[Submitted Version]
View
| Files available