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162 Publications
2023 | Published | Conference Paper | IST-REx-ID: 14460 | 
Nikdan, M., Pegolotti, T., Iofinova, E. B., Kurtic, E., & Alistarh, D.-A. (2023). SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 26215–26227). Honolulu, Hawaii, HI, United States: ML Research Press.
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2023 | Published | Conference Paper | IST-REx-ID: 17378 |
Frantar, E., Ashkboos, S., Hoefler, T., & Alistarh, D.-A. (2023). OPTQ: Accurate post-training quantization for generative pre-trained transformers. In 11th International Conference on Learning Representations . Kigali, Rwanda: International Conference on Learning Representations.
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2023 | Published | Conference Paper | IST-REx-ID: 14458 |
Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models can be accurately pruned in one-shot. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii, HI, United States: ML Research Press.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 12566 |
Alistarh, D.-A., Ellen, F., & Rybicki, J. (2023). Wait-free approximate agreement on graphs. Theoretical Computer Science. Elsevier. https://doi.org/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. (2023). CrAM: A Compression-Aware Minimizer. In 11th International Conference on Learning Representations . Kigali, Rwanda : OpenReview.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 15363 |
Safaryan, M., Krumes, A., & Alistarh, D.-A. (2023). Knowledge distillation performs partial variance reduction. In 36th Conference on Neural Information Processing Systems (Vol. 36). New Orleans, LA, United States.
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| arXiv
2023 | Published | Thesis | IST-REx-ID: 13074 |
Krumes, A. (2023). Efficiency and generalization of sparse neural networks. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:13074
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2023 | Published | Conference Paper | IST-REx-ID: 14771 |
Iofinova, E. B., Krumes, A., & Alistarh, D.-A. (2023). Bias in pruned vision models: In-depth analysis and countermeasures. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 24364–24373). Vancouver, BC, Canada: IEEE. https://doi.org/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. (2023). Quantized distributed training of large models with convergence guarantees. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 24020–24044). Honolulu, Hawaii, HI, United States: ML Research Press.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14364 |
Alistarh, D.-A., Aspnes, J., Ellen, F., Gelashvili, R., & Zhu, L. (2023). Why extension-based proofs fail. SIAM Journal on Computing. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/20M1375851
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 13262 |
Fedorov, A., Hashemi, D., Nadiradze, G., & Alistarh, D.-A. (2023). Provably-efficient and internally-deterministic parallel Union-Find. In Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures (pp. 261–271). Orlando, FL, United States: Association for Computing Machinery. https://doi.org/10.1145/3558481.3591082
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14260 |
Koval, N., Fedorov, A., Sokolova, M., Tsitelov, D., & Alistarh, D.-A. (2023). Lincheck: A practical framework for testing concurrent data structures on JVM. In 35th International Conference on Computer Aided Verification (Vol. 13964, pp. 156–169). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37706-8_8
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2023 | Research Data Reference | IST-REx-ID: 14995 |
Koval, N., Fedorov, A., Sokolova, M., Tsitelov, D., & Alistarh, D.-A. (2023). Lincheck: A practical framework for testing concurrent data structures on JVM. Zenodo. https://doi.org/10.5281/ZENODO.7877757
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2023 | Published | Book Chapter | IST-REx-ID: 19983 |
Balliu, A., Korhonen, J., Kuhn, F., Lievonen, H., Olivetti, D., Pai, S., … Uitto, J. (2023). Sinkless Orientation Made Simple. In Symposium on Simplicity in Algorithms (pp. 175–191). Florence, Italy: 2023 Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611977585.ch17
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14459 |
Shevchenko, A., Kögler, K., Hassani, H., & Mondelli, M. (2023). Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 11181 |
Brown, T. A., Sigouin, W., & Alistarh, D.-A. (2022). 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 (pp. 385–399). Seoul, Republic of Korea: Association for Computing Machinery. https://doi.org/10.1145/3503221.3508410
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2022 | Published | Conference Paper | IST-REx-ID: 17088 |
Kurtic, E., Campos, D., Nguyen, T., Frantar, E., Kurtz, M., Fineran, B., … Alistarh, D.-A. (2022). 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 (pp. 4163–4181). Abu Dhabi, United Arab Emirates: Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.emnlp-main.279
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 12182 |
Pacut, M., Parham, M., Rybicki, J., Schmid, S., Suomela, J., & Tereshchenko, A. (2022). Brief announcement: Temporal locality in online algorithms. In 36th International Symposium on Distributed Computing (Vol. 246). Augusta, GA, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/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. (2022). Local mending. In M. Parter (Ed.), International Colloquium on Structural Information and Communication Complexity (Vol. 13298, pp. 1–20). Paderborn, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-09993-9_1
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 11183 |
Nikabadi, A., & Korhonen, J. (2022). Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters. In Q. Bramas, V. Gramoli, & A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems (Vol. 217). Strasbourg, France: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.OPODIS.2021.15
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