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168 Publications
2018 |
Published |
Journal Article |
IST-REx-ID: 43 |
Rybicki, J., Kisdi, E., & Anttila, J. (2018). Model of bacterial toxin-dependent pathogenesis explains infective dose. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.1721061115
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2018 |
Published |
Conference Paper |
IST-REx-ID: 5965 |
Alistarh, D.-A., Brown, T. A., Kopinsky, J., Li, J. Z., & Nadiradze, G. (2018). Distributionally linearizable data structures. In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18 (pp. 133–142). Vienna, Austria: ACM. https://doi.org/10.1145/3210377.3210411
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| arXiv
2018 |
Published |
Journal Article |
IST-REx-ID: 536 |
Alistarh, D.-A., Aspnes, J., King, V., & Saia, J. (2018). Communication-efficient randomized consensus. Distributed Computing. Springer. https://doi.org/10.1007/s00446-017-0315-1
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2018 |
Published |
Conference Paper |
IST-REx-ID: 85 |
Gilad, E., Brown, T. A., Oskin, M., & Etsion, Y. (2018). Snapshot based synchronization: A fast replacement for Hand-over-Hand locking (Vol. 11014, pp. 465–479). Presented at the Euro-Par: European Conference on Parallel Processing, Turin, Italy: Springer. https://doi.org/10.1007/978-3-319-96983-1_33
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2017 |
Published |
Conference Paper |
IST-REx-ID: 791 |
Alistarh, D.-A., Kopinsky, J., Li, J., & Nadiradze, G. (2017). The power of choice in priority scheduling. In Proceedings of the ACM Symposium on Principles of Distributed Computing (Vol. Part F129314, pp. 283–292). Washington, WA, USA: ACM. https://doi.org/10.1145/3087801.3087810
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 487
Baig, G., Radunovic, B., Alistarh, D.-A., Balkwill, M., Karagiannis, T., & Qiu, L. (2017). Towards unlicensed cellular networks in TV white spaces. In Proceedings of the 2017 13th International Conference on emerging Networking EXperiments and Technologies (pp. 2–14). Incheon, South Korea: ACM. https://doi.org/10.1145/3143361.3143367
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2017 |
Published |
Conference Paper |
IST-REx-ID: 431 |
Alistarh, D.-A., Grubic, D., Li, J., Tomioka, R., & Vojnović, M. (2017). QSGD: Communication-efficient SGD via gradient quantization and encoding (Vol. 2017, pp. 1710–1721). Presented at the NIPS: Neural Information Processing System, Long Beach, CA, United States: Neural Information Processing Systems Foundation.
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| arXiv
2017 |
Published |
Conference Paper |
IST-REx-ID: 432 |
Zhang, H., Li, J., Kara, K., Alistarh, D.-A., Liu, J., & Zhang, C. (2017). ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning. In Proceedings of Machine Learning Research (Vol. 70, pp. 4035–4043). Sydney, Australia: ML Research Press.
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