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151 Publications
2018 | Published | Conference Paper | IST-REx-ID: 5962 | 
Alistarh, Dan-Adrian, Christopher De Sa, and Nikola H Konstantinov. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, 169–78. ACM, 2018. https://doi.org/10.1145/3212734.3212763.
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2018 | Published | Conference Paper | IST-REx-ID: 5961
Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine Learning.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, 487–88. ACM, 2018. https://doi.org/10.1145/3212734.3212798.
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2018 | Published | Conference Paper | IST-REx-ID: 5964 |
Aksenov, Vitaly, Dan-Adrian Alistarh, and Petr Kuznetsov. “Brief Announcement: Performance Prediction for Coarse-Grained Locking.” In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing - PODC ’18, 411–13. ACM, 2018. https://doi.org/10.1145/3212734.3212785.
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2018 | Published | Conference Paper | IST-REx-ID: 5965 |
Alistarh, Dan-Adrian, Trevor A Brown, Justin Kopinsky, Jerry Z. Li, and Giorgi Nadiradze. “Distributionally Linearizable Data Structures.” In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, 133–42. ACM, 2018. https://doi.org/10.1145/3210377.3210411.
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2018 | Published | Conference Paper | IST-REx-ID: 5966 |
Alistarh, Dan-Adrian, Syed Kamran Haider, Raphael Kübler, and Giorgi Nadiradze. “The Transactional Conflict Problem.” In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures - SPAA ’18, 383–92. ACM, 2018. https://doi.org/10.1145/3210377.3210406.
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2018 | Published | Conference Paper | IST-REx-ID: 6589 |
Alistarh, Dan-Adrian, Torsten Hoefler, Mikael Johansson, Nikola H Konstantinov, Sarit Khirirat, and Cedric Renggli. “The Convergence of Sparsified Gradient Methods.” In Advances in Neural Information Processing Systems 31, Volume 2018:5973–83. Neural Information Processing Systems Foundation, 2018.
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2018 | Published | Conference Paper | IST-REx-ID: 7812 |
Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “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, Ghufran, Bozidar Radunovic, Dan-Adrian Alistarh, Matthew Balkwill, Thomas Karagiannis, and Lili Qiu. “Towards Unlicensed Cellular Networks in TV White Spaces.” In Proceedings of the 2017 13th International Conference on Emerging Networking EXperiments and Technologies, 2–14. ACM, 2017. https://doi.org/10.1145/3143361.3143367.
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2017 | Published | Conference Paper | IST-REx-ID: 432 |
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
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2017 | Published | Conference Paper | IST-REx-ID: 431 |
Alistarh, Dan-Adrian, QSGD: Communication-efficient SGD via gradient quantization and encoding. 2017. 2017
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2017 | Published | Conference Paper | IST-REx-ID: 791 |
Alistarh, Dan-Adrian, Justin Kopinsky, Jerry Li, and Giorgi Nadiradze. “The Power of Choice in Priority Scheduling.” In Proceedings of the ACM Symposium on Principles of Distributed Computing, Part F129314:283–92. ACM, 2017. https://doi.org/10.1145/3087801.3087810.
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