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138 Publications
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.
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| 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.
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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.
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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.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 15363 |
Safaryan, Mher, Alexandra Krumes, and Dan-Adrian Alistarh. “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 |
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.
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2023 |Published| Conference Paper | IST-REx-ID: 13053 |
Krumes, Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert, and Dan-Adrian Alistarh. “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: 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.
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| 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.
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| arXiv
2023 |Published| Conference Paper | IST-REx-ID: 17378 |
Frantar, Elias, Saleh Ashkboos, Torsten Hoefler, and Dan-Adrian Alistarh. “OPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers.” In 11th International Conference on Learning Representations . International Conference on Learning Representations, 2023.
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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.
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| arXiv
2022 |Published| Conference Paper | IST-REx-ID: 11184 |
Alistarh, Dan-Adrian, Rati Gelashvili, and Joel Rybicki. “Fast Graphical Population Protocols.” In 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas, Vincent Gramoli, and Alessia Milani, Vol. 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.OPODIS.2021.14.
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| arXiv
2022 |Published| Conference Paper | IST-REx-ID: 11183 |
Nikabadi, Amir, and Janne Korhonen. “Beyond Distributed Subgraph Detection: Induced Subgraphs, Multicolored Problems and Graph Parameters.” In 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas, Vincent Gramoli, and Alessia Milani, Vol. 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.OPODIS.2021.15.
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2022 |Published| Conference Paper | IST-REx-ID: 12182 |
Pacut, Maciej, Mahmoud Parham, Joel Rybicki, Stefan Schmid, Jukka Suomela, and Aleksandr Tereshchenko. “Brief Announcement: Temporal Locality in Online Algorithms.” In 36th International Symposium on Distributed Computing, Vol. 246. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.DISC.2022.52.
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2022 |Published| Conference Paper | IST-REx-ID: 11844 |
Alistarh, Dan-Adrian, Joel Rybicki, and Sasha Voitovych. “Near-Optimal Leader Election in Population Protocols on Graphs.” In Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, 246–56. Association for Computing Machinery, 2022. https://doi.org/10.1145/3519270.3538435.
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| arXiv
2022 |Published| Conference Paper | IST-REx-ID: 11181 |
Brown, Trevor A, William Sigouin, and Dan-Adrian Alistarh. “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, 385–99. Association for Computing Machinery, 2022. https://doi.org/10.1145/3503221.3508410.
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2022 |Published| Conference Paper | IST-REx-ID: 11180 |
Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “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, 353–67. Association for Computing Machinery, 2022. https://doi.org/10.1145/3503221.3508432.
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2022 | Research Data Reference | IST-REx-ID: 13076 |
Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Zenodo, 2022. https://doi.org/10.5281/ZENODO.5733408.
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2022 |Published| Conference Paper | IST-REx-ID: 11707 |
Balliu, Alkida, Juho Hirvonen, Darya Melnyk, Dennis Olivetti, Joel Rybicki, and Jukka Suomela. “Local Mending.” In International Colloquium on Structural Information and Communication Complexity, edited by Merav Parter, 13298:1–20. LNCS. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-09993-9_1.
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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.
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