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151 Publications

2018 | Published | Conference Paper | IST-REx-ID: 5962 | OA
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
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
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 | OA
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
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 
2018 | Published | Conference Paper | IST-REx-ID: 5965 | OA
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
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2018 | Published | Conference Paper | IST-REx-ID: 5966 | OA
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
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2018 | Published | Conference Paper | IST-REx-ID: 6589 | OA
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.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 
2018 | Published | Conference Paper | IST-REx-ID: 7812 | OA
Polino A, Pascanu R, Alistarh D-A. Model compression via distillation and quantization. In: 6th International Conference on Learning Representations. ; 2018.
[Published Version] View | Files available | arXiv
 
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: 432 | OA
Zhang, Hantian, ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning. Proceedings of Machine Learning Research 70. 2017
[Submitted Version] View | Files available
 
2017 | Published | Conference Paper | IST-REx-ID: 431 | OA
Alistarh, Dan-Adrian, QSGD: Communication-efficient SGD via gradient quantization and encoding. 2017. 2017
[Submitted Version] View | Download Submitted Version (ext.) | arXiv
 
2017 | Published | Conference Paper | IST-REx-ID: 791 | OA
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
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 

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