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117 Publications


2022 | Research Data Reference | IST-REx-ID: 13076 | OA
Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” Zenodo, 2022. https://doi.org/10.5281/ZENODO.5733408.
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2022 | Published | Conference Paper | IST-REx-ID: 11180 | OA
Postnikova, Anastasiia, Nikita Koval, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Multi-Queues Can Be State-of-the-Art Priority Schedulers.” In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 353–67. Association for Computing Machinery, 2022. https://doi.org/10.1145/3503221.3508432.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 11181 | OA
Brown, Trevor A, William Sigouin, and Dan-Adrian Alistarh. “PathCAS: An Efficient Middle Ground for Concurrent Search Data Structures.” In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 385–99. Association for Computing Machinery, 2022. https://doi.org/10.1145/3503221.3508410.
[Published Version] View | Files available | DOI | WoS
 

2022 | Published | Conference Paper | IST-REx-ID: 11183 | OA
Nikabadi, Amir, and Janne Korhonen. “Beyond Distributed Subgraph Detection: Induced Subgraphs, Multicolored Problems and Graph Parameters.” In 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas, Vincent Gramoli, and Alessia Milani, Vol. 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.OPODIS.2021.15.
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2022 | Published | Conference Paper | IST-REx-ID: 11184 | OA
Alistarh, Dan-Adrian, Rati Gelashvili, and Joel Rybicki. “Fast Graphical Population Protocols.” In 25th International Conference on Principles of Distributed Systems, edited by Quentin Bramas, Vincent Gramoli, and Alessia Milani, Vol. 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.OPODIS.2021.14.
[Published Version] View | Files available | DOI | arXiv
 

2022 | Published | Journal Article | IST-REx-ID: 11420 | OA
Shevchenko, Aleksandr, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2022.
[Published Version] View | Files available | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 11707 | OA
Balliu, Alkida, Juho Hirvonen, Darya Melnyk, Dennis Olivetti, Joel Rybicki, and Jukka Suomela. “Local Mending.” In International Colloquium on Structural Information and Communication Complexity, edited by Merav Parter, 13298:1–20. LNCS. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-09993-9_1.
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2022 | Published | Conference Paper | IST-REx-ID: 11844 | OA
Alistarh, Dan-Adrian, Joel Rybicki, and Sasha Voitovych. “Near-Optimal Leader Election in Population Protocols on Graphs.” In Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, 246–56. Association for Computing Machinery, 2022. https://doi.org/10.1145/3519270.3538435.
[Published Version] View | Files available | DOI | arXiv
 

2022 | Published | Conference Paper | IST-REx-ID: 12182 | OA
Pacut, Maciej, Mahmoud Parham, Joel Rybicki, Stefan Schmid, Jukka Suomela, and Aleksandr Tereshchenko. “Brief Announcement: Temporal Locality in Online Algorithms.” In 36th International Symposium on Distributed Computing, Vol. 246. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.DISC.2022.52.
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2021 | Published | Journal Article | IST-REx-ID: 7939 | OA
Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.” Distributed Computing. Springer Nature, 2021. https://doi.org/10.1007/s00446-020-00380-5.
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2021 | Published | Journal Article | IST-REx-ID: 8286 | OA
Alistarh, Dan-Adrian, Giorgi Nadiradze, and Amirmojtaba Sabour. “Dynamic Averaging Load Balancing on Cycles.” Algorithmica. Springer Nature, 2021. https://doi.org/10.1007/s00453-021-00905-9.
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2021 | Published | Journal Article | IST-REx-ID: 8723 | OA
Li, Shigang, Tal Ben-Nun Tal Ben-Nun, Giorgi Nadiradze, Salvatore Di Girolamo, Nikoli Dryden, Dan-Adrian Alistarh, and Torsten Hoefler. “Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging.” IEEE Transactions on Parallel and Distributed Systems. IEEE, 2021. https://doi.org/10.1109/TPDS.2020.3040606.
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2021 | Published | Conference Paper | IST-REx-ID: 13147 | OA
Alimisis, Foivos, Peter Davies, and Dan-Adrian Alistarh. “Communication-Efficient Distributed Optimization with Quantized Preconditioners.” In Proceedings of the 38th International Conference on Machine Learning, 139:196–206. ML Research Press, 2021.
[Published Version] View | Files available | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 11436 | OA
Kungurtsev, Vyacheslav, Malcolm Egan, Bapi Chatterjee, and Dan-Adrian Alistarh. “Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees.” In 35th AAAI Conference on Artificial Intelligence, AAAI 2021, 35:8209–16. AAAI Press, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 11452 | OA
Alimisis, Foivos, Peter Davies, Bart Vandereycken, and Dan-Adrian Alistarh. “Distributed Principal Component Analysis with Limited Communication.” In Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, 4:2823–34. Neural Information Processing Systems Foundation, 2021.
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2021 | Published | Conference Paper | IST-REx-ID: 11458 | OA
Peste, Elena-Alexandra, Eugenia B Iofinova, Adrian Vladu, and Dan-Adrian Alistarh. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks.” In 35th Conference on Neural Information Processing Systems, 34:8557–70. Curran Associates, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 11463 | OA
Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient Matrix-Free Approximations of Second-Order Information.” In 35th Conference on Neural Information Processing Systems, 34:14873–86. Curran Associates, 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 11464 | OA
Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower Bounds for Distributed Optimisation.” In 35th Conference on Neural Information Processing Systems, 34:7254–66. Curran Associates, 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2021 | Published | Journal Article | IST-REx-ID: 9541 | OA
Czumaj, Artur, Peter Davies, and Merav Parter. “Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space.” ACM Transactions on Algorithms. Association for Computing Machinery, 2021. https://doi.org/10.1145/3451992.
[Submitted Version] View | Files available | DOI | Download Submitted Version (ext.) | WoS | arXiv
 

2021 | Published | Conference Paper | IST-REx-ID: 9543 | OA
Davies, Peter, Vijaykrishna Gurunanthan, Niusha Moshrefi, Saleh Ashkboos, and Dan-Adrian Alistarh. “New Bounds for Distributed Mean Estimation and Variance Reduction.” In 9th International Conference on Learning Representations, 2021.
[Published Version] View | Download Published Version (ext.) | arXiv
 

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