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.
122 Publications
2020 | Conference Paper | IST-REx-ID: 9415 | 
Kurtz, M., Kopinsky, J., Gelashvili, R., Matveev, A., Carr, J., Goin, M., … Alistarh, D.-A. (2020). Inducing and exploiting activation sparsity for fast neural network inference. In 37th International Conference on Machine Learning, ICML 2020 (Vol. 119, pp. 5533–5543). Online.
[Published Version]
View
| Files available
2020 | Journal Article | IST-REx-ID: 8268 |
Gurel, N. M., Kara, K., Stojanov, A., Smith, T., Lemmin, T., Alistarh, D.-A., … Zhang, C. (2020). Compressive sensing using iterative hard thresholding with low precision data representation: Theory and applications. IEEE Transactions on Signal Processing. IEEE. https://doi.org/10.1109/TSP.2020.3010355
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2020 | Conference Paper | IST-REx-ID: 8722 |
Li, S., Tal Ben-Nun, T. B.-N., Girolamo, S. D., Alistarh, D.-A., & Hoefler, T. (2020). Taming unbalanced training workloads in deep learning with partial collective operations. In Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (pp. 45–61). San Diego, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3332466.3374528
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2020 | Journal Article | IST-REx-ID: 7224 |
Rybicki, J., Abrego, N., & Ovaskainen, O. (2020). Habitat fragmentation and species diversity in competitive communities. Ecology Letters. Wiley. https://doi.org/10.1111/ele.13450
[Published Version]
View
| Files available
| DOI
| WoS
2020 | Conference Paper | IST-REx-ID: 8724 |
Konstantinov, N. H., Frantar, E., Alistarh, D.-A., & Lampert, C. (2020). On the sample complexity of adversarial multi-source PAC learning. In Proceedings of the 37th International Conference on Machine Learning (Vol. 119, pp. 5416–5425). Online: ML Research Press.
[Published Version]
View
| Files available
| arXiv
2020 | Conference Paper | IST-REx-ID: 7213 |
Bhatia, S., Chatterjee, B., Nathani, D., & Kaul, M. (2020). A persistent homology perspective to the link prediction problem. In Complex Networks and their applications VIII (Vol. 881, pp. 27–39). Lisbon, Portugal: Springer Nature. https://doi.org/10.1007/978-3-030-36687-2_3
[Submitted Version]
View
| Files available
| DOI
| WoS
2020 | Conference Paper | IST-REx-ID: 7802 |
Czumaj, A., Davies, P., & Parter, M. (2020). Graph sparsification for derandomizing massively parallel computation with low space. In Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020) (pp. 175–185). Virtual Event, United States: Association for Computing Machinery. https://doi.org/10.1145/3350755.3400282
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2020 | Conference Paper | IST-REx-ID: 7636 |
Brown, T. A., Prokopec, A., & Alistarh, D.-A. (2020). Non-blocking interpolation search trees with doubly-logarithmic running time. In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (pp. 276–291). San Diego, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3332466.3374542
[Published Version]
View
| DOI
| Download Published Version (ext.)
| WoS
2020 | Conference Paper | IST-REx-ID: 8191
Alistarh, D.-A., Brown, T. A., & Singhal, N. (2020). Memory tagging: Minimalist synchronization for scalable concurrent data structures. In Annual ACM Symposium on Parallelism in Algorithms and Architectures (pp. 37–49). Virtual Event, United States: Association for Computing Machinery. https://doi.org/10.1145/3350755.3400213
View
| DOI
| WoS
2020 | Conference Paper | IST-REx-ID: 7635
Koval, N., Sokolova, M., Fedorov, A., Alistarh, D.-A., & Tsitelov, D. (2020). Testing concurrency on the JVM with Lincheck. In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP (pp. 423–424). San Diego, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3332466.3374503
View
| DOI