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: 5947 | 
Chatterjee B, Peri S, Sa M, Singhal N. 2019. A simple and practical concurrent non-blocking unbounded graph with linearizable reachability queries. ACM International Conference Proceeding Series. ICDCN: Conference on Distributed Computing and Networking, 168–177.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Journal Article | IST-REx-ID: 6936 |
Ovaskainen O, Rybicki J, Abrego N. 2019. What can observational data reveal about metacommunity processes? Ecography. 42(11), 1877–1886.
[Published Version]
View
| Files available
| DOI
| WoS
2019 | Journal Article | IST-REx-ID: 6972 |
Lenzen C, Rybicki J. 2019. Self-stabilising Byzantine clock synchronisation is almost as easy as consensus. Journal of the ACM. 66(5), 32.
[Published Version]
View
| Files available
| DOI
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 7201 |
Renggli C, Ashkboos S, Aghagolzadeh M, Alistarh D-A, Hoefler T. 2019. SparCML: High-performance sparse communication for machine learning. International Conference for High Performance Computing, Networking, Storage and Analysis, SC. SC: Conference for High Performance Computing, Networking, Storage and Analysis, a11.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Journal Article | IST-REx-ID: 7214 |
Aganezov S, Zban I, Aksenov V, Alexeev N, Schatz MC. 2019. Recovering rearranged cancer chromosomes from karyotype graphs. BMC Bioinformatics. 20, 641.
[Published Version]
View
| Files available
| DOI
| WoS
2019 | Conference Paper | IST-REx-ID: 7437 |
Yu C, Tang H, Renggli C, Kassing S, Singla A, Alistarh D-A, Zhang C, Liu J. 2019. Distributed learning over unreliable networks. 36th International Conference on Machine Learning, ICML 2019. ICML: International Conference on Machine Learning vol. 2019–June, 12481–12512.
[Preprint]
View
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6673 |
Alistarh D-A, Nadiradze G, Koval N. 2019. Efficiency guarantees for parallel incremental algorithms under relaxed schedulers. 31st ACM Symposium on Parallelism in Algorithms and Architectures. SPAA: Symposium on Parallelism in Algorithms and Architectures, 145–154.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 7542 |
Wendler C, Alistarh D-A, Püschel M. 2019. Powerset convolutional neural networks. NIPS: Conference on Neural Information Processing Systems vol. 32, 927–938.
[Published Version]
View
| Download Published Version (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6935 |
Foerster K-T, Korhonen J, Rybicki J, Schmid S. 2019. Does preprocessing help under congestion? Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing. PODC: Symposium on Principles of Distributed Computing, 259–261.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6676 |
Alistarh D-A, Aspnes J, Ellen F, Gelashvili R, Zhu L. 2019. Why extension-based proofs fail. Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing. STOC: Symposium on Theory of Computing, 986–996.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2019 | Conference Paper | IST-REx-ID: 6933 |
Censor-Hillel K, Dory M, Korhonen J, Leitersdorf D. 2019. Fast approximate shortest paths in the congested clique. Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin. PODC: Symposium on Principles of Distributed Computing, 74–83.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2018 | Journal Article | IST-REx-ID: 536 |
Alistarh D-A, Aspnes J, King V, Saia J. 2018. Communication-efficient randomized consensus. Distributed Computing. 31(6), 489–501.
[Published Version]
View
| Files available
| DOI
2018 | Conference Paper | IST-REx-ID: 7116 |
Grubic D, Tam L, Alistarh D-A, Zhang C. 2018. Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study. Proceedings of the 21st International Conference on Extending Database Technology. EDBT: Conference on Extending Database Technology, 145–156.
[Published Version]
View
| Files available
| DOI
2018 | Journal Article | IST-REx-ID: 6001
Alistarh D-A, Leiserson W, Matveev A, Shavit N. 2018. ThreadScan: Automatic and scalable memory reclamation. ACM Transactions on Parallel Computing. 4(4), 18.
View
| Files available
| DOI
2018 | Conference Paper | IST-REx-ID: 7812 |
Polino A, Pascanu R, Alistarh D-A. 2018. Model compression via distillation and quantization. 6th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
[Published Version]
View
| Files available
| arXiv
2018 | Journal Article | IST-REx-ID: 43 |
Rybicki J, Kisdi E, Anttila J. 2018. Model of bacterial toxin-dependent pathogenesis explains infective dose. PNAS. 115(42), 10690–10695.
[Submitted Version]
View
| Files available
| DOI
| WoS