Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
151 Publications
2021 | Published | Conference Paper | IST-REx-ID: 11452 | 
Alimisis, F., Davies, P., Vandereycken, B., & Alistarh, D.-A. (2021). Distributed principal component analysis with limited communication. In Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems (Vol. 4, pp. 2823–2834). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10432 |
Nadiradze, G., Markov, I., Chatterjee, B., Kungurtsev, V., & Alistarh, D.-A. (2021). Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 9037–9045). Virtual.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10049 |
Klein, K., Pascual Perez, G., Walter, M., Kamath Hosdurg, C., Capretto, M., Cueto Noval, M., … Pietrzak, K. Z. (2021). Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In 2021 IEEE Symposium on Security and Privacy (pp. 268–284). San Francisco, CA, United States: IEEE. https://doi.org/10.1109/sp40001.2021.00035
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
2021 | Published | Conference Paper | IST-REx-ID: 11458 |
Krumes, A., Iofinova, E. B., Vladu, A., & Alistarh, D.-A. (2021). AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 8557–8570). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 11463 |
Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free approximations of second-order information. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 11464 |
Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower bounds for distributed optimisation. In 35th Conference on Neural Information Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Neural Information Processing Systems Foundation.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Journal Article | IST-REx-ID: 15271
Czumaj, A., Davies, P., & Parter, M. (2021). Simple, deterministic, constant-round coloring in congested clique and MPC. SIAM Journal on Computing. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/20m1366502
View
| DOI
2021 | Published | Conference Paper | IST-REx-ID: 10219 |
Korhonen, J., Paz, A., Rybicki, J., Schmid, S., & Suomela, J. (2021). Brief announcement: Sinkless orientation is hard also in the supported LOCAL model. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.58
[Published Version]
View
| Files available
| DOI
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10217 |
Alistarh, D.-A., Gelashvili, R., & Nadiradze, G. (2021). Lower bounds for shared-memory leader election under bounded write contention. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.4
[Published Version]
View
| Files available
| DOI
2021 | Published | Conference Paper | IST-REx-ID: 10216 |
Chatterjee, B., Peri, S., & Sa, M. (2021). Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds. In 35th International Symposium on Distributed Computing (Vol. 209). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2021.52
[Published Version]
View
| Files available
| DOI
| arXiv
2021 | Published | Thesis | IST-REx-ID: 10429 |
Nadiradze, G. (2021). On achieving scalability through relaxation. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10429
[Published Version]
View
| Files available
| DOI
2021 | Published | Journal Article | IST-REx-ID: 10180 |
Hoefler, T., Alistarh, D.-A., Ben-Nun, T., Dryden, N., & Krumes, A. (2021). Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks. Journal of Machine Learning Research. ML Research Press.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2020 | Published | 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 | Published | Conference Paper | IST-REx-ID: 8383
Alistarh, D.-A., Aspnes, J., Ellen, F., Gelashvili, R., & Zhu, L. (2020). Brief Announcement: Why Extension-Based Proofs Fail. In Proceedings of the 39th Symposium on Principles of Distributed Computing (pp. 54–56). Virtual, Italy: Association for Computing Machinery. https://doi.org/10.1145/3382734.3405743
View
| DOI
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 | Published | Conference Paper | IST-REx-ID: 7605 |
Alistarh, Dan-Adrian, In search of the fastest concurrent union-find algorithm. 23rd International Conference on Principles of Distributed Systems 153. 2020
[Published Version]
View
| Files available
| DOI
| arXiv
2020 | Published | Journal Article | IST-REx-ID: 8268 |
Gurel, Nezihe Merve, Compressive sensing using iterative hard thresholding with low precision data representation: Theory and applications. IEEE Transactions on Signal Processing 68. 2020
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 15074 |
Brandt, S., Keller, B., Rybicki, J., Suomela, J., & Uitto, J. (2020). Brief announcement: Efficient load-balancing through distributed token dropping. In 34th International Symposium on Distributed Computing (Vol. 179). Virtual: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2020.40
[Published Version]
View
| Files available
| DOI
| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 8725 |
Aksenov, V., Alistarh, D.-A., Drozdova, A., & Mohtashami, A. (2020). The splay-list: A distribution-adaptive concurrent skip-list. In 34th International Symposium on Distributed Computing (Vol. 179, p. 3:1-3:18). Freiburg, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.DISC.2020.3
[Published Version]
View
| Files available
| DOI
| arXiv
2020 | Published | 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