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156 Publications
2023 | Published | Conference Paper | IST-REx-ID: 14458 | 
Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 12566 |
Alistarh D-A, Ellen F, Rybicki J. Wait-free approximate agreement on graphs. Theoretical Computer Science. 2023;948(2). doi:10.1016/j.tcs.2023.113733
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2023 | Published | Conference Paper | IST-REx-ID: 13053 |
Krumes A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware Minimizer. In: 11th International Conference on Learning Representations . OpenReview; 2023.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 15363 |
Safaryan M, Krumes A, Alistarh D-A. Knowledge distillation performs partial variance reduction. In: 36th Conference on Neural Information Processing Systems. Vol 36. ; 2023.
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2023 | Published | Thesis | IST-REx-ID: 13074 |
Krumes A. Efficiency and generalization of sparse neural networks. 2023. doi:10.15479/at:ista:13074
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2023 | Published | Conference Paper | IST-REx-ID: 14771 |
Iofinova EB, Krumes A, Alistarh D-A. Bias in pruned vision models: In-depth analysis and countermeasures. In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2023:24364-24373. doi:10.1109/cvpr52729.2023.02334
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14461 |
Markov I, Vladu A, Guo Q, Alistarh D-A. Quantized distributed training of large models with convergence guarantees. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:24020-24044.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14364 |
Alistarh D-A, Aspnes J, Ellen F, Gelashvili R, Zhu L. Why extension-based proofs fail. SIAM Journal on Computing. 2023;52(4):913-944. doi:10.1137/20M1375851
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.
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2022 | Published | Conference Paper | IST-REx-ID: 11181 |
Brown TA, Sigouin W, Alistarh D-A. PathCAS: An efficient middle ground for concurrent search data structures. In: Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery; 2022:385-399. doi:10.1145/3503221.3508410
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2022 | Published | Conference Paper | IST-REx-ID: 17088 |
Kurtic E, Campos D, Nguyen T, et al. The optimal BERT surgeon: Scalable and accurate second-order pruning for large language models. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics; 2022:4163-4181. doi:10.18653/v1/2022.emnlp-main.279
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2022 | Published | Conference Paper | IST-REx-ID: 12182 |
Pacut M, Parham M, Rybicki J, Schmid S, Suomela J, Tereshchenko A. Brief announcement: Temporal locality in online algorithms. In: 36th International Symposium on Distributed Computing. Vol 246. 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 A, Hirvonen J, Melnyk D, Olivetti D, Rybicki J, Suomela J. Local mending. In: Parter M, ed. International Colloquium on Structural Information and Communication Complexity. Vol 13298. LNCS. Springer Nature; 2022:1-20. doi:10.1007/978-3-031-09993-9_1
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2022 | Published | Conference Paper | IST-REx-ID: 11183 |
Nikabadi A, Korhonen J. Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters. In: Bramas Q, Gramoli V, Milani A, eds. 25th International Conference on Principles of Distributed Systems. Vol 217. 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 A, Koval N, Nadiradze G, Alistarh D-A. Multi-queues can be state-of-the-art priority schedulers. In: Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery; 2022:353-367. doi:10.1145/3503221.3508432
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| arXiv
2022 | Research Data Reference | IST-REx-ID: 13076 |
Postnikova A, Koval N, Nadiradze G, Alistarh D-A. Multi-queues can be state-of-the-art priority schedulers. 2022. doi:10.5281/ZENODO.5733408
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2022 | Published | Conference Paper | IST-REx-ID: 17087 |
Frantar E, Singh SP, Alistarh D-A. Optimal brain compression: A framework for accurate post-training quantization and pruning. In: 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 E, Alistarh D-A. SPDY: Accurate pruning with speedup guarantees. In: 39th International Conference on Machine Learning. Vol 162. ML Research Press; 2022:6726-6743.
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2022 | Published | Conference Paper | IST-REx-ID: 11184 |
Alistarh D-A, Gelashvili R, Rybicki J. Fast graphical population protocols. In: Bramas Q, Gramoli V, Milani A, eds. 25th International Conference on Principles of Distributed Systems. Vol 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:10.4230/LIPIcs.OPODIS.2021.14
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12299 |
Iofinova EB, Krumes A, Kurtz M, Alistarh D-A. How well do sparse ImageNet models transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers; 2022:12256-12266. doi:10.1109/cvpr52688.2022.01195
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