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121 Publications

2023 | Conference Paper | IST-REx-ID: 14460 | OA
Nikdan, Mahdi, et al. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 26215–27.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14458 | OA
Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Journal Article | IST-REx-ID: 14364 | OA
Alistarh, Dan-Adrian, et al. “Why Extension-Based Proofs Fail.” SIAM Journal on Computing, vol. 52, no. 4, Society for Industrial and Applied Mathematics, 2023, pp. 913–44, doi:10.1137/20M1375851.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14771 | OA
Iofinova, Eugenia B., et al. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–73, doi:10.1109/cvpr52729.2023.02334.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2023 | Journal Article | IST-REx-ID: 14815 | OA
Beznosikov, Aleksandr, et al. “On Biased Compression for Distributed Learning.” Journal of Machine Learning Research, vol. 24, Journal of Machine Learning Research, 2023, pp. 1–50.
[Published Version] View | Files available | WoS | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14260 | OA
Koval, Nikita, et al. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” 35th International Conference on Computer Aided Verification , vol. 13964, Springer Nature, 2023, pp. 156–69, doi:10.1007/978-3-031-37706-8_8.
[Published Version] View | Files available | DOI
 
2023 | Research Data Reference | IST-REx-ID: 14995 | OA
Koval, Nikita, et al. Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM. Zenodo, 2023, doi:10.5281/ZENODO.7877757.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2023 | Conference Paper | IST-REx-ID: 13262 | OA
Fedorov, Alexander, et al. “Provably-Efficient and Internally-Deterministic Parallel Union-Find.” Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2023, pp. 261–71, doi:10.1145/3558481.3591082.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11184 | OA
Alistarh, Dan-Adrian, et al. “Fast Graphical Population Protocols.” 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas et al., vol. 217, 14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.OPODIS.2021.14.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11183 | OA
Nikabadi, Amir, and Janne Korhonen. “Beyond Distributed Subgraph Detection: Induced Subgraphs, Multicolored Problems and Graph Parameters.” 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas et al., vol. 217, 15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.OPODIS.2021.15.
[Published Version] View | Files available | DOI
 
2022 | Journal Article | IST-REx-ID: 11420 | OA
Shevchenko, Aleksandr, et al. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research, vol. 23, no. 130, Journal of Machine Learning Research, 2022, pp. 1–55.
[Published Version] View | Files available | arXiv
 
2022 | Conference Paper | IST-REx-ID: 12182 | OA
Pacut, Maciej, et al. “Brief Announcement: Temporal Locality in Online Algorithms.” 36th International Symposium on Distributed Computing, vol. 246, 52, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.DISC.2022.52.
[Published Version] View | Files available | DOI
 
2022 | Conference Paper | IST-REx-ID: 12780 | OA
Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–54, doi:10.1145/3528535.3565248.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11844 | OA
Alistarh, Dan-Adrian, et al. “Near-Optimal Leader Election in Population Protocols on Graphs.” Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2022, pp. 246–56, doi:10.1145/3519270.3538435.
[Published Version] View | Files available | DOI | arXiv
 
2022 | Conference Paper | IST-REx-ID: 11181 | OA
Brown, Trevor A., et al. “PathCAS: An Efficient Middle Ground for Concurrent Search Data Structures.” Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 385–99, doi:10.1145/3503221.3508410.
[Published Version] View | Files available | DOI | WoS
 
2022 | Conference Paper | IST-REx-ID: 11180 | OA
Postnikova, Anastasiia, et al. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 353–67, doi:10.1145/3503221.3508432.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Research Data Reference | IST-REx-ID: 13076 | OA
Postnikova, Anastasiia, et al. Multi-Queues Can Be State-of-the-Art Priority Schedulers. Zenodo, 2022, doi:10.5281/ZENODO.5733408.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2022 | Conference Paper | IST-REx-ID: 11707 | OA
Balliu, Alkida, et al. “Local Mending.” International Colloquium on Structural Information and Communication Complexity, edited by Merav Parter, vol. 13298, Springer Nature, 2022, pp. 1–20, doi:10.1007/978-3-031-09993-9_1.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2022 | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Journal Article | IST-REx-ID: 10180 | OA
Hoefler, Torsten, et al. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research, vol. 22, no. 241, Journal of Machine Learning Research, 2021, pp. 1–124.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

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