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168 Publications
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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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 |
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: 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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2017 |
Published |
Conference Paper |
IST-REx-ID: 791 |
Alistarh, Dan-Adrian, et al. “The Power of Choice in Priority Scheduling.” Proceedings of the ACM Symposium on Principles of Distributed Computing, vol. Part F129314, ACM, 2017, pp. 283–92, doi:10.1145/3087801.3087810.
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 487
Baig, Ghufran, et al. “Towards Unlicensed Cellular Networks in TV White Spaces.” Proceedings of the 2017 13th International Conference on Emerging Networking EXperiments and Technologies, ACM, 2017, pp. 2–14, doi:10.1145/3143361.3143367.
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2017 |
Published |
Conference Paper |
IST-REx-ID: 431 |
Alistarh, Dan-Adrian, et al. QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. Vol. 2017, Neural Information Processing Systems Foundation, 2017, pp. 1710–21.
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 432 |
Zhang, Hantian, et al. “ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning.” Proceedings of Machine Learning Research, vol. 70, ML Research Press, 2017, pp. 4035–43.
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