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158 Publications
2024 | Published | Conference Paper | IST-REx-ID: 17456 | 
Markov, Ilia, et al. “L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient Data-Parallel Deep Learning.” Proceedings of Machine Learning and Systems , edited by P. Gibbons et al., vol. 6, Association for Computing Machinery, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19518 |
Wu, Diyuan, et al. “The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19510 |
Modoranu, Ionut-Vlad, et al. “MICROADAM: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19511 |
Ashkboos, Saleh, et al. “QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19519 |
Malinovskii, Vladimir, et al. “PV-Tuning: Beyond Straight-through Estimation for Extreme LLM Compression.” 38th Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 17332 |
Kokorin, Ilya, et al. “Wait-Free Trees with Asymptotically-Efficient Range Queries.” 2024 IEEE International Parallel and Distributed Processing Symposium, IEEE, 2024, pp. 169–79, doi:10.1109/IPDPS57955.2024.00023.
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| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18070
Chatterjee, Bapi, et al. “Federated SGD with Local Asynchrony.” Proceedings of the 44th International Conference on Distributed Computing Systems, IEEE, 2024, pp. 857–68, doi:10.1109/ICDCS60910.2024.00084.
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2024 | Published | Thesis | IST-REx-ID: 17490 |
Markov, Ilia. Communication-Efficient Distributed Training of Deep Neural Networks : An Algorithms and Systems Perspective. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17490.
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2024 | Research Data Reference | IST-REx-ID: 19884 |
Frantar, Elias, et al. MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models. Zenodo, 2024, doi:10.5281/ZENODO.14213091.
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2024 | Published | Thesis | IST-REx-ID: 17465 |
Shevchenko, Alexander. High-Dimensional Limits in Artificial Neural Networks. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:17465.
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2024 | Published | Conference Paper | IST-REx-ID: 17469 |
Kögler, Kevin, et al. “Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth.” Proceedings of the 41st International Conference on Machine Learning, vol. 235, ML Research Press, 2024, pp. 24964–5015.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 13179 |
Koval, Nikita, et al. “CQS: A Formally-Verified Framework for Fair and Abortable Synchronization.” Proceedings of the ACM on Programming Languages, vol. 7, 116, Association for Computing Machinery , 2023, doi:10.1145/3591230.
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2023 | Published | Journal Article | IST-REx-ID: 12330 |
Aksenov, Vitalii, et al. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” Distributed Computing, vol. 36, Springer Nature, 2023, pp. 395–418, doi:10.1007/s00446-022-00441-x.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 12735 |
Koval, Nikita, et al. “Fast and Scalable Channels in Kotlin Coroutines.” Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2023, pp. 107–18, doi:10.1145/3572848.3577481.
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| arXiv
2023 | Published | Conference Poster | IST-REx-ID: 12736 |
Aksenov, Vitaly, et al. “Unexpected Scaling in Path Copying Trees.” Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2023, pp. 438–40, doi:10.1145/3572848.3577512.
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2023 | Published | Journal Article | IST-REx-ID: 14815 |
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.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14460 |
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.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 17378 |
Frantar, Elias, et al. “OPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers.” 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.” Proceedings of the 40th International Conference on Machine Learning, vol. 202, ML Research Press, 2023, pp. 10323–37.
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| arXiv
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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