Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).

We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.

118 Publications


2024 | Conference Paper | IST-REx-ID: 15011 | OA
Kurtic, Eldar, Torsten Hoefler, and Dan-Adrian Alistarh. “How to Prune Your Language Model: Recovering Accuracy on the ‘Sparsity May Cry’ Benchmark.” In Proceedings of Machine Learning Research, 234:542–53. ML Research Press, 2024.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 12735 | OA
Koval, Nikita, Dan-Adrian Alistarh, and Roman Elizarov. “Fast and Scalable Channels in Kotlin Coroutines.” In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 107–18. Association for Computing Machinery, 2023. https://doi.org/10.1145/3572848.3577481.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Poster | IST-REx-ID: 12736 | OA
Aksenov, Vitaly, Trevor A Brown, Alexander Fedorov, and Ilya Kokorin. Unexpected Scaling in Path Copying Trees. Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery, 2023. https://doi.org/10.1145/3572848.3577512.
[Published Version] View | DOI | Download Published Version (ext.)
 

2023 | Conference Paper | IST-REx-ID: 13053 | OA
Peste, Elena-Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert, and Dan-Adrian Alistarh. “CrAM: A Compression-Aware Minimizer.” In 11th International Conference on Learning Representations , n.d.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 13179 | OA
Koval, Nikita, Dmitry Khalanskiy, and Dan-Adrian Alistarh. “CQS: A Formally-Verified Framework for Fair and Abortable Synchronization.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery , 2023. https://doi.org/10.1145/3591230.
[Published Version] View | Files available | DOI
 

2023 | Journal Article | IST-REx-ID: 12566 | OA
Alistarh, Dan-Adrian, Faith Ellen, and Joel Rybicki. “Wait-Free Approximate Agreement on Graphs.” Theoretical Computer Science. Elsevier, 2023. https://doi.org/10.1016/j.tcs.2023.113733.
[Published Version] View | Files available | DOI | WoS
 

2023 | Thesis | IST-REx-ID: 13074 | OA
Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural Networks.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:13074.
[Published Version] View | Files available | DOI
 

2023 | Journal Article | IST-REx-ID: 12330 | OA
Aksenov, Vitalii, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” Distributed Computing. Springer Nature, 2023. https://doi.org/10.1007/s00446-022-00441-x.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14461 | OA
Markov, Ilia, Adrian Vladu, Qi Guo, and Dan-Adrian Alistarh. “Quantized Distributed Training of Large Models with Convergence Guarantees.” In Proceedings of the 40th International Conference on Machine Learning, 202:24020–44. ML Research Press, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14459 | OA
Shevchenko, Aleksandr, Kevin Kögler, Hamed Hassani, and Marco Mondelli. “Fundamental Limits of Two-Layer Autoencoders, and Achieving Them with Gradient Methods.” In Proceedings of the 40th International Conference on Machine Learning, 202:31151–209. ML Research Press, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14460 | OA
Nikdan, Mahdi, Tommaso Pegolotti, Eugenia B Iofinova, Eldar Kurtic, and Dan-Adrian Alistarh. “SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge.” In Proceedings of the 40th International Conference on Machine Learning, 202:26215–27. ML Research Press, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14458 | OA
Frantar, Elias, and Dan-Adrian Alistarh. “SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot.” In Proceedings of the 40th International Conference on Machine Learning, 202:10323–37. ML Research Press, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 14364 | OA
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.” SIAM Journal on Computing. Society for Industrial and Applied Mathematics, 2023. https://doi.org/10.1137/20M1375851.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14771 | OA
Iofinova, Eugenia B, Elena-Alexandra Peste, and Dan-Adrian Alistarh. “Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures.” In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 24364–73. IEEE, 2023. https://doi.org/10.1109/cvpr52729.2023.02334.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Journal Article | IST-REx-ID: 14815 | OA
Beznosikov, Aleksandr, Samuel Horvath, Peter Richtarik, and Mher Safaryan. “On Biased Compression for Distributed Learning.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2023.
[Published Version] View | Files available | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14260 | OA
Koval, Nikita, Alexander Fedorov, Maria Sokolova, Dmitry Tsitelov, and Dan-Adrian Alistarh. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” In 35th International Conference on Computer Aided Verification , 13964:156–69. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37706-8_8.
[Published Version] View | Files available | DOI
 

2023 | Research Data Reference | IST-REx-ID: 14995 | OA
Koval, Nikita, Alexander Fedorov, Maria Sokolova, Dmitry Tsitelov, and Dan-Adrian Alistarh. “Lincheck: A Practical Framework for Testing Concurrent Data Structures on JVM.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.7877757.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

2023 | Conference Paper | IST-REx-ID: 13262 | OA
Fedorov, Alexander, Diba Hashemi, Giorgi Nadiradze, and Dan-Adrian Alistarh. “Provably-Efficient and Internally-Deterministic Parallel Union-Find.” In Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, 261–71. Association for Computing Machinery, 2023. https://doi.org/10.1145/3558481.3591082.
[Published Version] View | Files available | DOI | arXiv
 

2022 | 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 | 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.
[Published Version] View | Files available | DOI
 

2022 | 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 | 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.
[Published Version] View | Files available | DOI
 

2022 | Conference Paper | IST-REx-ID: 12780 | OA
Markov, Ilia, Hamidreza Ramezanikebrya, and Dan-Adrian Alistarh. “CGX: Adaptive System Support for Communication-Efficient Deep Learning.” In Proceedings of the 23rd ACM/IFIP International Middleware Conference, 241–54. Association for Computing Machinery, 2022. https://doi.org/10.1145/3528535.3565248.
[Published Version] View | Files available | DOI | arXiv
 

2022 | 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 | 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 | 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 | 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.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

2022 | 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.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2022 | Conference Paper | IST-REx-ID: 12299 | OA
Iofinova, Eugenia B, Elena-Alexandra Peste, Mark Kurtz, and Dan-Adrian Alistarh. “How Well Do Sparse ImageNet Models Transfer?” In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 12256–66. Institute of Electrical and Electronics Engineers, 2022. https://doi.org/10.1109/cvpr52688.2022.01195.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2021 | Journal Article | IST-REx-ID: 10180 | OA
Hoefler, Torsten, Dan-Adrian Alistarh, Tal Ben-Nun, Nikoli Dryden, and Elena-Alexandra Peste. “Sparsity in Deep Learning: Pruning and Growth for Efficient Inference and Training in Neural Networks.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10218 | OA
Alistarh, Dan-Adrian, Rati Gelashvili, and Joel Rybicki. “Brief Announcement: Fast Graphical Population Protocols.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.43.
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10217 | OA
Alistarh, Dan-Adrian, Rati Gelashvili, and Giorgi Nadiradze. “Lower Bounds for Shared-Memory Leader Election under Bounded Write Contention.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.4.
[Published Version] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 10216 | OA
Chatterjee, Bapi, Sathya Peri, and Muktikanta Sa. “Brief Announcement: Non-Blocking Dynamic Unbounded Graphs with Worst-Case Amortized Bounds.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.52.
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10219 | OA
Korhonen, Janne, Ami Paz, Joel Rybicki, Stefan Schmid, and Jukka Suomela. “Brief Announcement: Sinkless Orientation Is Hard Also in the Supported LOCAL Model.” In 35th International Symposium on Distributed Computing, Vol. 209. Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.DISC.2021.58.
[Published Version] View | Files available | DOI | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10853 | OA
Fedorov, Alexander, Nikita Koval, and Dan-Adrian Alistarh. “A Scalable Concurrent Algorithm for Dynamic Connectivity.” In Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, 208–20. Association for Computing Machinery, 2021. https://doi.org/10.1145/3409964.3461810.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | 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 | 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.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2021 | 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 | 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 | 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
 

2021 | Conference Paper | IST-REx-ID: 9620 | OA
Alistarh, Dan-Adrian, and Peter Davies. “Collecting Coupons Is Faster with Friends.” In Structural Information and Communication Complexity, 12810:3–12. Springer Nature, 2021. https://doi.org/10.1007/978-3-030-79527-6_1.
[Preprint] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 9823 | OA
Alistarh, Dan-Adrian, Faith Ellen, and Joel Rybicki. “Wait-Free Approximate Agreement on Graphs.” In Structural Information and Communication Complexity, 12810:87–105. Springer Nature, 2021. https://doi.org/10.1007/978-3-030-79527-6_6.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | 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 | 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 | 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.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2021 | Journal Article | IST-REx-ID: 9827 | OA
Chatterjee, Bapi, Ivan Walulya, and Philippas Tsigas. “Concurrent Linearizable Nearest Neighbour Search in LockFree-KD-Tree.” Theoretical Computer Science. Elsevier, 2021. https://doi.org/10.1016/j.tcs.2021.06.041.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2021 | Conference Paper | IST-REx-ID: 9951
Alistarh, Dan-Adrian, Martin Töpfer, and Przemysław Uznański. “Comparison Dynamics in Population Protocols.” In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, 55–65. Association for Computing Machinery, 2021. https://doi.org/10.1145/3465084.3467915.
View | DOI | WoS
 

2021 | Conference Paper | IST-REx-ID: 9935 | OA
Czumaj, Artur, Peter Davies, and Merav Parter. “Improved Deterministic (Δ+1) Coloring in Low-Space MPC.” In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, 469–479. Association for Computing Machinery, 2021. https://doi.org/10.1145/3465084.3467937.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS
 

2021 | Conference Paper | IST-REx-ID: 9933 | OA
Czumaj, Artur, Peter Davies, and Merav Parter. “Component Stability in Low-Space Massively Parallel Computation.” In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing, 481–491. Association for Computing Machinery, 2021. https://doi.org/10.1145/3465084.3467903.
[Submitted Version] View | DOI | Download Submitted Version (ext.) | WoS | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10432 | OA
Nadiradze, Giorgi, Ilia Markov, Bapi Chatterjee, Vyacheslav Kungurtsev, and Dan-Adrian Alistarh. “Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:9037–45, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10049 | OA
Klein, Karen, Guillermo Pascual Perez, Michael Walter, Chethan Kamath Hosdurg, Margarita Capretto, Miguel Cueto Noval, Ilia Markov, Michelle X Yeo, Joel F Alwen, and Krzysztof Z Pietrzak. “Keep the Dirt: Tainted TreeKEM, Adaptively and Actively Secure Continuous Group Key Agreement.” In 2021 IEEE Symposium on Security and Privacy , 268–84. IEEE, 2021. https://doi.org/10.1109/sp40001.2021.00035.
[Preprint] View | Files available | DOI | Download Preprint (ext.)
 

2021 | Conference Paper | IST-REx-ID: 10854 | OA
Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 71–72. Association for Computing Machinery, 2021. https://doi.org/10.1145/3410220.3453923.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Journal Article | IST-REx-ID: 10855 | OA
Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery, 2021. https://doi.org/10.1145/3447384.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Thesis | IST-REx-ID: 10429 | OA
Nadiradze, Giorgi. “On Achieving Scalability through Relaxation.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10429.
[Published Version] View | Files available | DOI
 

2021 | Conference Paper | IST-REx-ID: 10435 | OA
Nadiradze, Giorgi, Amirmojtaba Sabour, Peter Davies, Shigang Li, and Dan-Adrian Alistarh. “Asynchronous Decentralized SGD with Quantized and Local Updates.” In 35th Conference on Neural Information Processing Systems. Neural Information Processing Systems Foundation, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | 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 | Conference Paper | IST-REx-ID: 9678 | OA
Brandt, Sebastian, Barbara Keller, Joel Rybicki, Jukka Suomela, and Jara Uitto. “Efficient Load-Balancing through Distributed Token Dropping.” In Annual ACM Symposium on Parallelism in Algorithms and Architectures, 129–39, 2021. https://doi.org/10.1145/3409964.3461785.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | 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.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2021 | Journal Article | IST-REx-ID: 9571 | OA
Ramezani-Kebrya, Ali, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan-Adrian Alistarh, and Daniel M. Roy. “NUQSGD: Provably Communication-Efficient Data-Parallel SGD via Nonuniform Quantization.” Journal of Machine Learning Research. Journal of Machine Learning Research, 2021.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | 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.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | WoS | arXiv
 

2021 | Journal Article | IST-REx-ID: 15271
Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC.” SIAM Journal on Computing. Society for Industrial & Applied Mathematics, 2021. https://doi.org/10.1137/20m1366502.
View | DOI
 

2020 | Conference Paper | IST-REx-ID: 7272 | OA
Arbel-Raviv, Maya, Trevor A Brown, and Adam Morrison. “Getting to the Root of Concurrent Binary Search Tree Performance.” In Proceedings of the 2018 USENIX Annual Technical Conference, 295–306. USENIX Association, 2020.
[Published Version] View | Download Published Version (ext.)
 

2020 | Conference Paper | IST-REx-ID: 7605 | OA
Alistarh, Dan-Adrian, Alexander Fedorov, and Nikita Koval. “In Search of the Fastest Concurrent Union-Find Algorithm.” In 23rd International Conference on Principles of Distributed Systems, 153:15:1-15:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.OPODIS.2019.15.
[Published Version] View | Files available | DOI | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7803 | OA
Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in the Congested Clique.” In Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing, 309–18. Association for Computing Machinery, 2020. https://doi.org/10.1145/3382734.3405751.
[Submitted Version] View | Files available | DOI | arXiv
 

2020 | Conference Paper | IST-REx-ID: 8725 | OA
Aksenov, Vitaly, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.” In 34th International Symposium on Distributed Computing, 179:3:1-3:18. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.DISC.2020.3.
[Published Version] View | Files available | DOI | arXiv
 

2020 | Conference Paper | IST-REx-ID: 9632 | OA
Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression.” In Advances in Neural Information Processing Systems, 33:18098–109. Curran Associates, 2020.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2020 | Conference Paper | IST-REx-ID: 9631 | OA
Aksenov, Vitaly, Dan-Adrian Alistarh, and Janne Korhonen. “Scalable Belief Propagation via Relaxed Scheduling.” In Advances in Neural Information Processing Systems, 33:22361–72. Curran Associates, 2020.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2020 | Conference Paper | IST-REx-ID: 9415 | OA
Kurtz, Mark, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” In 37th International Conference on Machine Learning, ICML 2020, 119:5533–43, 2020.
[Published Version] View | Files available
 

2020 | Journal Article | IST-REx-ID: 8268 | OA
Gurel, Nezihe Merve, Kaan Kara, Alen Stojanov, Tyler Smith, Thomas Lemmin, Dan-Adrian Alistarh, Markus Puschel, and Ce Zhang. “Compressive Sensing Using Iterative Hard Thresholding with Low Precision Data Representation: Theory and Applications.” IEEE Transactions on Signal Processing. IEEE, 2020. https://doi.org/10.1109/TSP.2020.3010355.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2020 | Conference Paper | IST-REx-ID: 8722 | OA
Li, Shigang, Tal Ben-Nun Tal Ben-Nun, Salvatore Di Girolamo, Dan-Adrian Alistarh, and Torsten Hoefler. “Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations.” In Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 45–61. Association for Computing Machinery, 2020. https://doi.org/10.1145/3332466.3374528.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2020 | Journal Article | IST-REx-ID: 7224 | OA
Rybicki, Joel, Nerea Abrego, and Otso Ovaskainen. “Habitat Fragmentation and Species Diversity in Competitive Communities.” Ecology Letters. Wiley, 2020. https://doi.org/10.1111/ele.13450.
[Published Version] View | Files available | DOI | WoS
 

2020 | Conference Paper | IST-REx-ID: 8724 | OA
Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” In Proceedings of the 37th International Conference on Machine Learning, 119:5416–25. ML Research Press, 2020.
[Published Version] View | Files available | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7213 | OA
Bhatia, Sumit, Bapi Chatterjee, Deepak Nathani, and Manohar Kaul. “A Persistent Homology Perspective to the Link Prediction Problem.” In Complex Networks and Their Applications VIII, 881:27–39. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-36687-2_3.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Conference Paper | IST-REx-ID: 7802 | OA
Czumaj, Artur, Peter Davies, and Merav Parter. “Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space.” In Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020), 175–85. Association for Computing Machinery, 2020. https://doi.org/10.1145/3350755.3400282.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2020 | Conference Paper | IST-REx-ID: 7636 | OA
Brown, Trevor A, Aleksandar Prokopec, and Dan-Adrian Alistarh. “Non-Blocking Interpolation Search Trees with Doubly-Logarithmic Running Time.” In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 276–91. Association for Computing Machinery, 2020. https://doi.org/10.1145/3332466.3374542.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 

2020 | Conference Paper | IST-REx-ID: 8191
Alistarh, Dan-Adrian, Trevor A Brown, and Nandini Singhal. “Memory Tagging: Minimalist Synchronization for Scalable Concurrent Data Structures.” In Annual ACM Symposium on Parallelism in Algorithms and Architectures, 37–49. Association for Computing Machinery, 2020. https://doi.org/10.1145/3350755.3400213.
View | DOI | WoS
 

2020 | Conference Paper | IST-REx-ID: 7635
Koval, Nikita, Mariia Sokolova, Alexander Fedorov, Dan-Adrian Alistarh, and Dmitry Tsitelov. “Testing Concurrency on the JVM with Lincheck.” In Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, 423–24. Association for Computing Machinery, 2020. https://doi.org/10.1145/3332466.3374503.
View | DOI
 

2020 | Conference Paper | IST-REx-ID: 8383
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Brief Announcement: Why Extension-Based Proofs Fail.” In Proceedings of the 39th Symposium on Principles of Distributed Computing, 54–56. Association for Computing Machinery, 2020. https://doi.org/10.1145/3382734.3405743.
View | DOI
 

2020 | Conference Paper | IST-REx-ID: 15074 | OA
Brandt, Sebastian, Barbara Keller, Joel Rybicki, Jukka Suomela, and Jara Uitto. “Brief Announcement: Efficient Load-Balancing through Distributed Token Dropping.” In 34th International Symposium on Distributed Computing, Vol. 179. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.DISC.2020.40.
[Published Version] View | Files available | DOI | arXiv
 

2020 | Conference Paper | IST-REx-ID: 15077 | OA
Alistarh, Dan-Adrian, Giorgi Nadiradze, and Amirmojtaba Sabour. “Dynamic Averaging Load Balancing on Cycles.” In 47th International Colloquium on Automata, Languages, and Programming, Vol. 168. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.ICALP.2020.7.
[Published Version] View | Files available | DOI | arXiv
 

2019 | Journal Article | IST-REx-ID: 6759 | OA
Jelínek, Vít, and Martin Töpfer. “On Grounded L-Graphs and Their Relatives.” Electronic Journal of Combinatorics. Electronic Journal of Combinatorics, 2019. https://doi.org/10.37236/8096.
[Published Version] View | Files available | DOI | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6931 | OA
Nowak, Thomas, and Joel Rybicki. “Byzantine Approximate Agreement on Graphs.” In 33rd International Symposium on Distributed Computing, 146:29:1--29:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. https://doi.org/10.4230/LIPICS.DISC.2019.29.
[Published Version] View | Files available | DOI | arXiv
 

2019 | Conference Paper | IST-REx-ID: 5947 | OA
Chatterjee, Bapi, Sathya Peri, Muktikanta Sa, and Nandini Singhal. “A Simple and Practical Concurrent Non-Blocking Unbounded Graph with Linearizable Reachability Queries.” In ACM International Conference Proceeding Series, 168–77. ACM, 2019. https://doi.org/10.1145/3288599.3288617.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Poster | IST-REx-ID: 6485
Koval, Nikita, Dan-Adrian Alistarh, and Roman Elizarov. Lock-Free Channels for Programming via Communicating Sequential Processes. Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming. ACM Press, 2019. https://doi.org/10.1145/3293883.3297000.
View | DOI | WoS
 

2019 | Journal Article | IST-REx-ID: 6936 | OA
Ovaskainen, Otso, Joel Rybicki, and Nerea Abrego. “What Can Observational Data Reveal about Metacommunity Processes?” Ecography. Wiley, 2019. https://doi.org/10.1111/ecog.04444.
[Published Version] View | Files available | DOI | WoS
 

2019 | Journal Article | IST-REx-ID: 6972 | OA
Lenzen, Christoph, and Joel Rybicki. “Self-Stabilising Byzantine Clock Synchronisation Is Almost as Easy as Consensus.” Journal of the ACM. ACM, 2019. https://doi.org/10.1145/3339471.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 7122
Khirirat, Sarit, Mikael Johansson, and Dan-Adrian Alistarh. “Gradient Compression for Communication-Limited Convex Optimization.” In 2018 IEEE Conference on Decision and Control. IEEE, 2019. https://doi.org/10.1109/cdc.2018.8619625.
View | DOI | WoS
 

2019 | Conference Paper | IST-REx-ID: 7201 | OA
Renggli, Cedric, Saleh Ashkboos, Mehdi Aghagolzadeh, Dan-Adrian Alistarh, and Torsten Hoefler. “SparCML: High-Performance Sparse Communication for Machine Learning.” In International Conference for High Performance Computing, Networking, Storage and Analysis, SC. ACM, 2019. https://doi.org/10.1145/3295500.3356222.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Journal Article | IST-REx-ID: 7214 | OA
Aganezov, Sergey, Ilya Zban, Vitalii Aksenov, Nikita Alexeev, and Michael C. Schatz. “Recovering Rearranged Cancer Chromosomes from Karyotype Graphs.” BMC Bioinformatics. BMC, 2019. https://doi.org/10.1186/s12859-019-3208-4.
[Published Version] View | Files available | DOI | WoS
 

2019 | Conference Paper | IST-REx-ID: 7228
Koval, Nikita, Dan-Adrian Alistarh, and Roman Elizarov. “Scalable FIFO Channels for Programming via Communicating Sequential Processes.” In 25th Anniversary of Euro-Par, 11725:317–33. Springer Nature, 2019. https://doi.org/10.1007/978-3-030-29400-7_23.
View | DOI | WoS
 

2019 | Conference Paper | IST-REx-ID: 7437 | OA
Yu, Chen, Hanlin Tang, Cedric Renggli, Simon Kassing, Ankit Singla, Dan-Adrian Alistarh, Ce Zhang, and Ji Liu. “Distributed Learning over Unreliable Networks.” In 36th International Conference on Machine Learning, ICML 2019, 2019–June:12481–512. IMLS, 2019.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6673 | OA
Alistarh, Dan-Adrian, Giorgi Nadiradze, and Nikita Koval. “Efficiency Guarantees for Parallel Incremental Algorithms under Relaxed Schedulers.” In 31st ACM Symposium on Parallelism in Algorithms and Architectures, 145–54. ACM Press, 2019. https://doi.org/10.1145/3323165.3323201.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 7542 | OA
Wendler, Chris, Dan-Adrian Alistarh, and Markus Püschel. “Powerset Convolutional Neural Networks,” 32:927–38. Neural Information Processing Systems Foundation, 2019.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6935 | OA
Foerster, Klaus-Tycho, Janne Korhonen, Joel Rybicki, and Stefan Schmid. “Does Preprocessing Help under Congestion?” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, 259–61. ACM, 2019. https://doi.org/10.1145/3293611.3331581.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6676 | OA
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.” In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 986–96. ACM Press, 2019. https://doi.org/10.1145/3313276.3316407.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Conference Paper | IST-REx-ID: 6933 | OA
Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, 74–83. ACM, 2019. https://doi.org/10.1145/3293611.3331633.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2018 | Journal Article | IST-REx-ID: 536 | OA
Alistarh, Dan-Adrian, James Aspnes, Valerie King, and Jared Saia. “Communication-Efficient Randomized Consensus.” Distributed Computing. Springer, 2018. https://doi.org/10.1007/s00446-017-0315-1.
[Published Version] View | Files available | DOI
 

2018 | Conference Paper | IST-REx-ID: 7116 | OA
Grubic, Demjan, Leo Tam, Dan-Adrian Alistarh, and Ce Zhang. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.” In Proceedings of the 21st International Conference on Extending Database Technology, 145–56. OpenProceedings, 2018. https://doi.org/10.5441/002/EDBT.2018.14.
[Published Version] View | Files available | DOI
 

2018 | Journal Article | IST-REx-ID: 6001
Alistarh, Dan-Adrian, William Leiserson, Alexander Matveev, and Nir Shavit. “ThreadScan: Automatic and Scalable Memory Reclamation.” ACM Transactions on Parallel Computing. Association for Computing Machinery, 2018. https://doi.org/10.1145/3201897.
View | Files available | DOI
 

2018 | Conference Paper | IST-REx-ID: 7812 | OA
Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “Model Compression via Distillation and Quantization.” In 6th International Conference on Learning Representations, 2018.
[Published Version] View | Files available | arXiv
 

Filters and Search Terms

department=DaAl

Search

Filter Publications