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121 Publications
2022 | Journal Article | IST-REx-ID: 11420 | 
Shevchenko, Aleksandr, et al. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research, vol. 23, no. 130, Journal of Machine Learning Research, 2022, pp. 1–55.
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2022 | Conference Paper | IST-REx-ID: 12182 |
Pacut, Maciej, et al. “Brief Announcement: Temporal Locality in Online Algorithms.” 36th International Symposium on Distributed Computing, vol. 246, 52, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.DISC.2022.52.
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2022 | Conference Paper | IST-REx-ID: 12780 |
Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–54, doi:10.1145/3528535.3565248.
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2022 | Conference Paper | IST-REx-ID: 11844 |
Alistarh, Dan-Adrian, et al. “Near-Optimal Leader Election in Population Protocols on Graphs.” Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2022, pp. 246–56, doi:10.1145/3519270.3538435.
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2022 | Conference Paper | IST-REx-ID: 11181 |
Brown, Trevor A., et al. “PathCAS: An Efficient Middle Ground for Concurrent Search Data Structures.” Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 385–99, doi:10.1145/3503221.3508410.
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2022 | Conference Paper | IST-REx-ID: 11180 |
Postnikova, Anastasiia, et al. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 353–67, doi:10.1145/3503221.3508432.
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2022 | Research Data Reference | IST-REx-ID: 13076 |
Postnikova, Anastasiia, et al. Multi-Queues Can Be State-of-the-Art Priority Schedulers. Zenodo, 2022, doi:10.5281/ZENODO.5733408.
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2022 | Conference Paper | IST-REx-ID: 11707 |
Balliu, Alkida, et al. “Local Mending.” International Colloquium on Structural Information and Communication Complexity, edited by Merav Parter, vol. 13298, Springer Nature, 2022, pp. 1–20, doi:10.1007/978-3-031-09993-9_1.
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2022 | Conference Paper | IST-REx-ID: 12299 |
Iofinova, Eugenia B., et al. “How Well Do Sparse ImageNet Models Transfer?” 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–66, doi:10.1109/cvpr52688.2022.01195.
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2021 | Journal Article | IST-REx-ID: 10180 |
Hoefler, Torsten, et al. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research, vol. 22, no. 241, Journal of Machine Learning Research, 2021, pp. 1–124.
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