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164 Publications
2021 |
Published |
Conference Paper |
IST-REx-ID: 9823 |
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.
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| arXiv
2021 |
Published |
Journal Article |
IST-REx-ID: 9827 |
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.
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2021 |
Published |
Conference Paper |
IST-REx-ID: 9933 |
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.
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| arXiv
2021 |
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Conference Paper |
IST-REx-ID: 9935 |
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.
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2021 |
Published |
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.
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2020 |
Published |
Conference Paper |
IST-REx-ID: 15074 |
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.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 15077 |
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.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 15086 |
Faghri, Fartash , Iman Tabrizian, Ilia Markov, Dan-Adrian Alistarh, Daniel Roy, and Ali Ramezani-Kebrya. “Adaptive Gradient Quantization for Data-Parallel SGD.” In Advances in Neural Information Processing Systems, Vol. 33. Neural Information Processing Systems Foundation, 2020.
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| arXiv
2020 |
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Conference Paper |
IST-REx-ID: 7802 |
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.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 7803 |
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.
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| arXiv
2020 |
Published |
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.
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2020 |
Published |
Journal Article |
IST-REx-ID: 8268 |
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.
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| arXiv
2020 |
Published |
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.
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2020 |
Published |
Conference Paper |
IST-REx-ID: 8722 |
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.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 8724 |
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.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 8725 |
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.
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| arXiv
2020 |
Conference Paper |
IST-REx-ID: 9415 |
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.
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2020 |
Published |
Conference Paper |
IST-REx-ID: 9631 |
Aksenov, Vitaly, Dan-Adrian Alistarh, and Janne Korhonen. “Scalable Belief Propagation via Relaxed Scheduling,” 33:22361–72. Neural Information Processing Systems Foundation, 2020.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 9632 |
Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression,” 33:18098–109. Neural Information Processing Systems Foundation, 2020.
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| arXiv
2020 |
Published |
Conference Paper |
IST-REx-ID: 7213 |
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.
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