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.
151 Publications
2021 | Published | Conference Paper | IST-REx-ID: 11452 | 
Alimisis, Foivos, Peter Davies, Bart Vandereycken, and Dan-Adrian Alistarh. “Distributed Principal Component Analysis with Limited Communication.” In Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, 4:2823–34. Neural Information Processing Systems Foundation, 2021.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10432 |
Nadiradze, Giorgi, Ilia Markov, Bapi Chatterjee, Vyacheslav Kungurtsev, and Dan-Adrian Alistarh. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:9037–45, 2021.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 10049 |
Klein, Karen, Guillermo Pascual Perez, Michael Walter, Chethan Kamath Hosdurg, Margarita Capretto, Miguel Cueto Noval, Ilia Markov, Michelle X Yeo, Joel F Alwen, and Krzysztof Z Pietrzak. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” In 2021 IEEE Symposium on Security and Privacy , 268–84. IEEE, 2021. 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, Alexandra, Eugenia B Iofinova, Adrian Vladu, and Dan-Adrian Alistarh. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” In 35th Conference on Neural Information Processing Systems, 34:8557–70. Neural Information Processing Systems Foundation, 2021.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 11463 |
Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient Matrix-Free Approximations of Second-Order Information.” In 35th Conference on Neural Information Processing Systems, 34:14873–86. Neural Information Processing Systems Foundation, 2021.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 11464 |
Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower Bounds for Distributed Optimisation.” In 35th Conference on Neural Information Processing Systems, 34:7254–66. Neural Information Processing Systems Foundation, 2021.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
2021 | Published | Journal Article | IST-REx-ID: 15271
Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC.” SIAM Journal on Computing. Society for Industrial and Applied Mathematics, 2021. https://doi.org/10.1137/20m1366502.
View
| DOI
2021 | Published | Conference Paper | IST-REx-ID: 10219 |
Korhonen, Janne, Ami Paz, Joel Rybicki, Stefan Schmid, and Jukka Suomela. “Brief Announcement: Sinkless Orientation Is Hard Also in the Supported LOCAL Model.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. 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, Dan-Adrian, Rati Gelashvili, and Giorgi Nadiradze. “Lower Bounds for Shared-Memory Leader Election under Bounded Write Contention.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.4.
[Published Version]
View
| Files available
| DOI
2021 | Published | Conference Paper | IST-REx-ID: 10216 |
Chatterjee, Bapi, Sathya Peri, and Muktikanta Sa. “Brief Announcement: Non-Blocking Dynamic Unbounded Graphs with Worst-Case Amortized Bounds.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.52.
[Published Version]
View
| Files available
| DOI
| arXiv
2021 | Published | Thesis | IST-REx-ID: 10429 |
Nadiradze, Giorgi. “On Achieving Scalability through Relaxation.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10429.
[Published Version]
View
| Files available
| DOI
2021 | Published | Journal Article | IST-REx-ID: 10180 |
Hoefler, Torsten, Dan-Adrian Alistarh, Tal Ben-Nun, Nikoli Dryden, and Alexandra Krumes. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research. ML Research Press, 2021.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 8191
Alistarh, Dan-Adrian, Trevor A Brown, and Nandini Singhal. “Memory Tagging: Minimalist Synchronization for Scalable Concurrent Data Structures.” In Annual ACM Symposium on Parallelism in Algorithms and Architectures, 37–49. Association for Computing Machinery, 2020. https://doi.org/10.1145/3350755.3400213.
View
| DOI
| WoS
2020 | Published | Conference Paper | IST-REx-ID: 8383
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Brief Announcement: Why Extension-Based Proofs Fail.” In Proceedings of the 39th Symposium on Principles of Distributed Computing, 54–56. Association for Computing Machinery, 2020. https://doi.org/10.1145/3382734.3405743.
View
| DOI
2020 | Conference Paper | IST-REx-ID: 9415 |
Kurtz, Mark, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” In 37th International Conference on Machine Learning, ICML 2020, 119:5533–43, 2020.
[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, Sebastian, Barbara Keller, Joel Rybicki, Jukka Suomela, and Jara Uitto. “Brief Announcement: Efficient Load-Balancing through Distributed Token Dropping.” In 34th International Symposium on Distributed Computing, Vol. 179. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. 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, Vitaly, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” In 34th International Symposium on Distributed Computing, 179:3:1-3:18. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. 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, Shigang, Tal Ben-Nun Tal Ben-Nun, Salvatore Di Girolamo, Dan-Adrian Alistarh, and Torsten Hoefler. “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, 45–61. Association for Computing Machinery, 2020. https://doi.org/10.1145/3332466.3374528.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv