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156 Publications
2018 | Published | Journal Article | IST-REx-ID: 536 | 
Alistarh D-A, Aspnes J, King V, Saia J. Communication-efficient randomized consensus. Distributed Computing. 2018;31(6):489-501. doi:10.1007/s00446-017-0315-1
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2018 | Published | Journal Article | IST-REx-ID: 76 |
Lenzen C, Rybicki J. Near-optimal self-stabilising counting and firing squads. Distributed Computing. 2018. doi:10.1007/s00446-018-0342-6
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2018 | Published | Conference Paper | IST-REx-ID: 85 |
Gilad E, Brown TA, Oskin M, Etsion Y. Snapshot based synchronization: A fast replacement for Hand-over-Hand locking. In: Vol 11014. Springer; 2018:465-479. doi:10.1007/978-3-319-96983-1_33
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2018 | Published | Journal Article | IST-REx-ID: 43 |
Rybicki J, Kisdi E, Anttila J. Model of bacterial toxin-dependent pathogenesis explains infective dose. Proceedings of the National Academy of Sciences of the United States of America. 2018;115(42):10690-10695. doi:10.1073/pnas.1721061115
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2018 | Published | Conference Paper | IST-REx-ID: 5963 |
Alistarh D-A, Brown TA, Kopinsky J, Nadiradze G. Relaxed schedulers can efficiently parallelize iterative algorithms. In: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18. ACM; 2018:377-386. doi:10.1145/3212734.3212756
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 5962 |
Alistarh D-A, De Sa C, Konstantinov NH. The convergence of stochastic gradient descent in asynchronous shared memory. In: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18. ACM; 2018:169-178. doi:10.1145/3212734.3212763
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2018 | Published | Conference Paper | IST-REx-ID: 5961
Alistarh D-A. A brief tutorial on distributed and concurrent machine learning. In: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18. ACM; 2018:487-488. doi:10.1145/3212734.3212798
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2018 | Published | Conference Paper | IST-REx-ID: 5964 |
Aksenov V, Alistarh D-A, Kuznetsov P. Brief Announcement: Performance prediction for coarse-grained locking. In: Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18. ACM; 2018:411-413. doi:10.1145/3212734.3212785
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2018 | Published | Conference Paper | IST-REx-ID: 5965 |
Alistarh D-A, Brown TA, Kopinsky J, Li JZ, Nadiradze G. Distributionally linearizable data structures. In: Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18. ACM; 2018:133-142. doi:10.1145/3210377.3210411
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2018 | Published | Conference Paper | IST-REx-ID: 5966 |
Alistarh D-A, Haider SK, Kübler R, Nadiradze G. The transactional conflict problem. In: Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18. ACM; 2018:383-392. doi:10.1145/3210377.3210406
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 6589 |
Alistarh D-A, Hoefler T, Johansson M, Konstantinov NH, Khirirat S, Renggli C. The convergence of sparsified gradient methods. In: Advances in Neural Information Processing Systems 31. Vol Volume 2018. Neural Information Processing Systems Foundation; 2018:5973-5983.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 7812 |
Polino A, Pascanu R, Alistarh D-A. Model compression via distillation and quantization. In: 6th International Conference on Learning Representations. ; 2018.
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2017 | Published | Conference Paper | IST-REx-ID: 487
Baig G, Radunovic B, Alistarh D-A, Balkwill M, Karagiannis T, Qiu L. Towards unlicensed cellular networks in TV white spaces. In: Proceedings of the 2017 13th International Conference on Emerging Networking EXperiments and Technologies. ACM; 2017:2-14. doi:10.1145/3143361.3143367
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2017 | Published | Conference Paper | IST-REx-ID: 791 |
Alistarh D-A, Kopinsky J, Li J, Nadiradze G. The power of choice in priority scheduling. In: Proceedings of the ACM Symposium on Principles of Distributed Computing. Vol Part F129314. ACM; 2017:283-292. doi:10.1145/3087801.3087810
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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. 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. ML Research Press; 2017:4035-4043.
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2017 | Published | Conference Paper | IST-REx-ID: 431 |
Alistarh D-A, Grubic D, Li J, Tomioka R, Vojnović M. QSGD: Communication-efficient SGD via gradient quantization and encoding. In: Vol 2017. Neural Information Processing Systems Foundation; 2017:1710-1721.
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