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164 Publications
2019 |
Published |
Conference Paper |
IST-REx-ID: 7437 |
Yu, Chen, et al. “Distributed Learning over Unreliable Networks.” 36th International Conference on Machine Learning, ICML 2019, vol. 2019–June, IMLS, 2019, pp. 12481–512.
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| arXiv
2019 |
Published |
Conference Paper |
IST-REx-ID: 7542 |
Wendler, Chris, et al. Powerset Convolutional Neural Networks. Vol. 32, Neural Information Processing Systems Foundation, 2019, pp. 927–38.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 7812 |
Polino, Antonio, et al. “Model Compression via Distillation and Quantization.” 6th International Conference on Learning Representations, 2018.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 85 |
Gilad, Eran, et al. Snapshot Based Synchronization: A Fast Replacement for Hand-over-Hand Locking. Vol. 11014, Springer, 2018, pp. 465–79, doi:10.1007/978-3-319-96983-1_33.
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2018 |
Published |
Journal Article |
IST-REx-ID: 536 |
Alistarh, Dan-Adrian, et al. “Communication-Efficient Randomized Consensus.” Distributed Computing, vol. 31, no. 6, Springer, 2018, pp. 489–501, doi:10.1007/s00446-017-0315-1.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 5961
Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine Learning.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM, 2018, pp. 487–88, doi:10.1145/3212734.3212798.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 5962 |
Alistarh, Dan-Adrian, et al. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM, 2018, pp. 169–78, doi:10.1145/3212734.3212763.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 5963 |
Alistarh, Dan-Adrian, et al. “Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM, 2018, pp. 377–86, doi:10.1145/3212734.3212756.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 5964 |
Aksenov, Vitaly, et al. “Brief Announcement: Performance Prediction for Coarse-Grained Locking.” Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, ACM, 2018, pp. 411–13, doi:10.1145/3212734.3212785.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 5965 |
Alistarh, Dan-Adrian, et al. “Distributionally Linearizable Data Structures.” Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, ACM, 2018, pp. 133–42, doi:10.1145/3210377.3210411.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 5966 |
Alistarh, Dan-Adrian, et al. “The Transactional Conflict Problem.” Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, ACM, 2018, pp. 383–92, doi:10.1145/3210377.3210406.
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| arXiv
2018 |
Published |
Journal Article |
IST-REx-ID: 6001
Alistarh, Dan-Adrian, et al. “ThreadScan: Automatic and Scalable Memory Reclamation.” ACM Transactions on Parallel Computing, vol. 4, no. 4, 18, Association for Computing Machinery, 2018, doi:10.1145/3201897.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 6031
Stojanov, Alen, et al. “Fast Quantized Arithmetic on X86: Trading Compute for Data Movement.” 2018 IEEE International Workshop on Signal Processing Systems, vol. 2018–October, 8598402, IEEE, 2018, doi:10.1109/SiPS.2018.8598402.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 6558 |
Alistarh, Dan-Adrian, et al. “Byzantine Stochastic Gradient Descent.” Advances in Neural Information Processing Systems, vol. 2018, Neural Information Processing Systems Foundation, 2018, pp. 4613–23.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 6589 |
Alistarh, Dan-Adrian, et al. “The Convergence of Sparsified Gradient Methods.” Advances in Neural Information Processing Systems 31, vol. Volume 2018, Neural Information Processing Systems Foundation, 2018, pp. 5973–83.
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| arXiv
2018 |
Published |
Conference Paper |
IST-REx-ID: 7116 |
Grubic, Demjan, et al. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.” Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–56, doi:10.5441/002/EDBT.2018.14.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 7123 |
Alistarh, Dan-Adrian, et al. “Space-Optimal Majority in Population Protocols.” Proceedings of the 29th Annual ACM-SIAM Symposium on Discrete Algorithms, ACM, 2018, pp. 2221–39, doi:10.1137/1.9781611975031.144.
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| arXiv
2018 |
Published |
Journal Article |
IST-REx-ID: 76 |
Lenzen, Christoph, and Joel Rybicki. “Near-Optimal Self-Stabilising Counting and Firing Squads.” Distributed Computing, Springer, 2018, doi:10.1007/s00446-018-0342-6.
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2018 |
Published |
Conference Paper |
IST-REx-ID: 397
Arbel Raviv, Maya, and Trevor A. Brown. Harnessing Epoch-Based Reclamation for Efficient Range Queries. Vol. 53, no. 1, ACM, 2018, pp. 14–27, doi:10.1145/3178487.3178489.
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2018 |
Published |
Journal Article |
IST-REx-ID: 43 |
Rybicki, Joel, et al. “Model of Bacterial Toxin-Dependent Pathogenesis Explains Infective Dose.” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 42, National Academy of Sciences, 2018, pp. 10690–95, doi:10.1073/pnas.1721061115.
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