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138 Publications
2022 |Published| Journal Article | IST-REx-ID: 8286 | 
Alistarh D-A, Nadiradze G, Sabour A. Dynamic averaging load balancing on cycles. Algorithmica. 2022;84(4):1007-1029. doi:10.1007/s00453-021-00905-9
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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: 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| Journal Article | IST-REx-ID: 11420 |
Shevchenko A, Kungurtsev V, Mondelli M. Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. 2022;23(130):1-55.
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2022 |Published| Conference Paper | IST-REx-ID: 12780 |
Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for communication-efficient deep learning. In: Proceedings of the 23rd ACM/IFIP International Middleware Conference. Association for Computing Machinery; 2022:241-254. doi:10.1145/3528535.3565248
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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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2021 |Published| Journal Article | IST-REx-ID: 10180 |
Hoefler T, Alistarh D-A, Ben-Nun T, Dryden N, Peste E-A. Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks. Journal of Machine Learning Research. 2021;22(241):1-124.
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2021 |Published| Conference Paper | IST-REx-ID: 10218 |
Alistarh D-A, Gelashvili R, Rybicki J. Brief announcement: Fast graphical population protocols. In: 35th International Symposium on Distributed Computing. Vol 209. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2021. doi:10.4230/LIPIcs.DISC.2021.43
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2021 |Published| Conference Paper | IST-REx-ID: 10217 |
Alistarh D-A, Gelashvili R, Nadiradze G. Lower bounds for shared-memory leader election under bounded write contention. In: 35th International Symposium on Distributed Computing. Vol 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik; 2021. doi:10.4230/LIPIcs.DISC.2021.4
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2021 |Published| Conference Paper | IST-REx-ID: 10216 |
Chatterjee B, Peri S, Sa M. Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds. In: 35th International Symposium on Distributed Computing. Vol 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik; 2021. doi:10.4230/LIPIcs.DISC.2021.52
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2021 |Published| Conference Paper | IST-REx-ID: 10219 |
Korhonen J, Paz A, Rybicki J, Schmid S, Suomela J. Brief announcement: Sinkless orientation is hard also in the supported LOCAL model. In: 35th International Symposium on Distributed Computing. Vol 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik; 2021. doi:10.4230/LIPIcs.DISC.2021.58
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2021 |Published| Conference Paper | IST-REx-ID: 10853 |
Fedorov A, Koval N, Alistarh D-A. A scalable concurrent algorithm for dynamic connectivity. In: Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery; 2021:208-220. doi:10.1145/3409964.3461810
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2021 |Published| Conference Paper | IST-REx-ID: 11436 |
Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. Asynchronous optimization methods for efficient training of deep neural networks with guarantees. In: 35th AAAI Conference on Artificial Intelligence, AAAI 2021. Vol 35. AAAI Press; 2021:8209-8216.
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2021 |Published| Conference Paper | IST-REx-ID: 11452 |
Alimisis F, Davies P, Vandereycken B, Alistarh D-A. Distributed principal component analysis with limited communication. In: Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems. Vol 4. Neural Information Processing Systems Foundation; 2021:2823-2834.
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2021 |Published| Conference Paper | IST-REx-ID: 11463 |
Frantar E, Kurtic E, Alistarh D-A. M-FAC: Efficient matrix-free approximations of second-order information. In: 35th Conference on Neural Information Processing Systems. Vol 34. Curran Associates; 2021:14873-14886.
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2021 |Published| Conference Paper | IST-REx-ID: 11464 |
Alistarh D-A, Korhonen J. Towards tight communication lower bounds for distributed optimisation. In: 35th Conference on Neural Information Processing Systems. Vol 34. Curran Associates; 2021:7254-7266.
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2021 |Published| Conference Paper | IST-REx-ID: 9543 |
Davies P, Gurunanthan V, Moshrefi N, Ashkboos S, Alistarh D-A. New bounds for distributed mean estimation and variance reduction. In: 9th International Conference on Learning Representations. ; 2021.
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2021 |Published| Conference Paper | IST-REx-ID: 9620 |
Alistarh D-A, Davies P. Collecting coupons is faster with friends. In: Structural Information and Communication Complexity. Vol 12810. Springer Nature; 2021:3-12. doi:10.1007/978-3-030-79527-6_1
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2021 |Published| Conference Paper | IST-REx-ID: 9823 |
Alistarh D-A, Ellen F, Rybicki J. Wait-free approximate agreement on graphs. In: Structural Information and Communication Complexity. Vol 12810. Springer Nature; 2021:87-105. doi:10.1007/978-3-030-79527-6_6
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2021 |Published| Conference Paper | IST-REx-ID: 11458 |
Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed training of deep neural networks. In: 35th Conference on Neural Information Processing Systems. Vol 34. Curran Associates; 2021:8557-8570.
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