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.
117 Publications
2024 | Published | Conference Paper | IST-REx-ID: 15011 | 
Kurtic, Eldar, Torsten Hoefler, and Dan-Adrian Alistarh. “How to Prune Your Language Model: Recovering Accuracy on the ‘Sparsity May Cry’ Benchmark.” In Proceedings of Machine Learning Research, 234:542–53. ML Research Press, 2024.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Journal Article | IST-REx-ID: 12330 |
Aksenov, Vitalii, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” Distributed Computing. Springer Nature, 2023. https://doi.org/10.1007/s00446-022-00441-x.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2023 | Published | Journal Article | IST-REx-ID: 12566 |
Alistarh, Dan-Adrian, Faith Ellen, and Joel Rybicki. “Wait-Free Approximate Agreement on Graphs.” Theoretical Computer Science. Elsevier, 2023. https://doi.org/10.1016/j.tcs.2023.113733.
[Published Version]
View
| Files available
| DOI
| WoS
2023 | Published | Conference Paper | IST-REx-ID: 12735 |
Koval, Nikita, Dan-Adrian Alistarh, and Roman Elizarov. “Fast and Scalable Channels in Kotlin Coroutines.” In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 107–18. Association for Computing Machinery, 2023. https://doi.org/10.1145/3572848.3577481.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Poster | IST-REx-ID: 12736 |
Aksenov, Vitaly, Trevor A Brown, Alexander Fedorov, and Ilya Kokorin. Unexpected Scaling in Path Copying Trees. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery, 2023. https://doi.org/10.1145/3572848.3577512.
[Published Version]
View
| DOI
| Download Published Version (ext.)
2023 | Accepted | Conference Paper | IST-REx-ID: 13053 |
Peste, Elena-Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert, and Dan-Adrian Alistarh. “CrAM: A Compression-Aware Minimizer.” In 11th International Conference on Learning Representations , n.d.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2023 | Published | Thesis | IST-REx-ID: 13074 |
Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural Networks.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:13074.
[Published Version]
View
| Files available
| DOI
2023 | Published | Journal Article | IST-REx-ID: 13179 |
Koval, Nikita, Dmitry Khalanskiy, and Dan-Adrian Alistarh. “CQS: A Formally-Verified Framework for Fair and Abortable Synchronization.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery , 2023. https://doi.org/10.1145/3591230.
[Published Version]
View
| Files available
| DOI
2023 | Published | Conference Paper | IST-REx-ID: 13262 |
Fedorov, Alexander, Diba Hashemi, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Provably-Efficient and Internally-Deterministic Parallel Union-Find.” In Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, 261–71. Association for Computing Machinery, 2023. https://doi.org/10.1145/3558481.3591082.
[Published Version]
View
| Files available
| DOI
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14260 |
Koval, Nikita, Alexander Fedorov, Maria Sokolova, Dmitry Tsitelov, and Dan-Adrian Alistarh. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” In 35th International Conference on Computer Aided Verification , 13964:156–69. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37706-8_8.
[Published Version]
View
| Files available
| DOI
2023 | Published | Journal Article | IST-REx-ID: 14364 |
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.” SIAM Journal on Computing. Society for Industrial and Applied Mathematics, 2023. https://doi.org/10.1137/20M1375851.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14458 |
Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14460 |
Nikdan, Mahdi, Tommaso Pegolotti, Eugenia B Iofinova, Eldar Kurtic, and Dan-Adrian Alistarh. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” In Proceedings of the 40th International Conference on Machine Learning, 202:26215–27. ML Research Press, 2023.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov, Ilia, Adrian Vladu, Qi Guo, and Dan-Adrian Alistarh. “Quantized Distributed Training of Large Models with Convergence Guarantees.” In Proceedings of the 40th International Conference on Machine Learning, 202:24020–44. ML Research Press, 2023.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14771 |
Iofinova, Eugenia B, Elena-Alexandra Peste, and Dan-Adrian Alistarh. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 24364–73. IEEE, 2023. https://doi.org/10.1109/cvpr52729.2023.02334.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14815 |
Beznosikov, Aleksandr, Samuel Horvath, Peter Richtarik, and Mher Safaryan. “On Biased Compression for Distributed Learning.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2023.
[Published Version]
View
| Files available
| WoS
| arXiv
2023 | Research Data Reference | IST-REx-ID: 14995 |
Koval, Nikita, Alexander Fedorov, Maria Sokolova, Dmitry Tsitelov, and Dan-Adrian Alistarh. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.7877757.
[Published Version]
View
| Files available
| DOI
| Download Published Version (ext.)
2022 | Published | Conference Paper | IST-REx-ID: 12299 |
Iofinova, Eugenia B, Elena-Alexandra Peste, Mark Kurtz, and Dan-Adrian Alistarh. “How Well Do Sparse ImageNet Models Transfer?” In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 12256–66. Institute of Electrical and Electronics Engineers, 2022. https://doi.org/10.1109/cvpr52688.2022.01195.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12780 |
Markov, Ilia, Hamidreza Ramezanikebrya, and Dan-Adrian Alistarh. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” In Proceedings of the 23rd ACM/IFIP International Middleware Conference, 241–54. Association for Computing Machinery, 2022. https://doi.org/10.1145/3528535.3565248.
[Published Version]
View
| Files available
| DOI
| arXiv