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156 Publications
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.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37.
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2023 | Published | Journal Article | IST-REx-ID: 12566 |
Alistarh, Dan-Adrian, et al. “Wait-Free Approximate Agreement on Graphs.” Theoretical Computer Science, vol. 948, no. 2, 113733, Elsevier, 2023, doi:10.1016/j.tcs.2023.113733.
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2023 | Published | Conference Paper | IST-REx-ID: 13053 |
Krumes, Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th International Conference on Learning Representations , OpenReview, 2023.
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2023 | Published | Conference Paper | IST-REx-ID: 15363 |
Safaryan, Mher, et al. “Knowledge Distillation Performs Partial Variance Reduction.” 36th Conference on Neural Information Processing Systems, vol. 36, 2023.
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2023 | Published | Thesis | IST-REx-ID: 13074 |
Krumes, Alexandra. Efficiency and Generalization of Sparse Neural Networks. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:13074.
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2023 | Published | Conference Paper | IST-REx-ID: 14771 |
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.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov, Ilia, et al. “Quantized Distributed Training of Large Models with Convergence Guarantees.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 24020–44.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14364 |
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.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, Alexander, et al. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 31151–209.
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2022 | Published | Conference Paper | IST-REx-ID: 11181 |
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.
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2022 | Published | Conference Paper | IST-REx-ID: 17088 |
Kurtic, Eldar, et al. “The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models.” Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2022, pp. 4163–81, doi:10.18653/v1/2022.emnlp-main.279.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12182 |
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.
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2022 | Published | Conference Paper | IST-REx-ID: 11707 |
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.
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2022 | Published | Conference Paper | IST-REx-ID: 11183 |
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.
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2022 | Published | Conference Paper | IST-REx-ID: 11180 |
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.
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| arXiv
2022 | Research Data Reference | IST-REx-ID: 13076 |
Postnikova, Anastasiia, et al. Multi-Queues Can Be State-of-the-Art Priority Schedulers. Zenodo, 2022, doi:10.5281/ZENODO.5733408.
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2022 | Published | Conference Paper | IST-REx-ID: 17087 |
Frantar, Elias, et al. “Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning.” 36th Conference on Neural Information Processing Systems, vol. 35, ML Research Press, 2022.
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2022 | Published | Conference Paper | IST-REx-ID: 17059 |
Frantar, Elias, and Dan-Adrian Alistarh. “SPDY: Accurate Pruning with Speedup Guarantees.” 39th International Conference on Machine Learning, vol. 162, ML Research Press, 2022, pp. 6726–43.
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2022 | Published | Conference Paper | IST-REx-ID: 11184 |
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.
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2022 | Published | Conference Paper | IST-REx-ID: 12299 |
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.
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