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.
LibreCat: https://research-explorer.ista.ac.at/record/9571
arXiv: 1908.06077

Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.”https://doi.org/10.1007/s00446-020-00380-5__Distributed Computing. Springer Nature, 2021.https://doi.org/10.1007/s00446-020-00380-5 .
LibreCat: https://research-explorer.ista.ac.at/record/7939
DOI: 10.1007/s00446-020-00380-5
WoS: 000556444600001
arXiv: 1903.05956

Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC.”https://doi.org/10.1137/20m1366502__SIAM Journal on Computing. Society for Industrial &; Applied Mathematics, 2021.https://doi.org/10.1137/20m1366502 .
LibreCat: https://research-explorer.ista.ac.at/record/15271
DOI: 10.1137/20m1366502

Czumaj, Artur, and Peter Davies. “Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks.”https://doi.org/10.1145/3446383__Journal of the ACM. Association for Computing Machinery, 2021.https://doi.org/10.1145/3446383 .
LibreCat: https://research-explorer.ista.ac.at/record/15267
DOI: 10.1145/3446383
arXiv: 1703.01859

Alimisis, Foivos, Antonio Orvieto, Gary Becigneul, and Aurelien Lucchi. “Momentum Improves Optimization on Riemannian Manifolds.” In Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 130:1351–59. ML Research Press, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/15263
arXiv: 2002.04144

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.
LibreCat: https://research-explorer.ista.ac.at/record/7272

Alistarh, Dan-Adrian, Alexander Fedorov, and Nikita Koval. “In Search of the Fastest Concurrent Union-Find Algorithm.”https://doi.org/10.4230/LIPIcs.OPODIS.2019.15__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 .
LibreCat: https://research-explorer.ista.ac.at/record/7605
DOI: 10.4230/LIPIcs.OPODIS.2019.15
arXiv: 1911.06347

Czumaj, Artur, Peter Davies, and Merav Parter. “Simple, Deterministic, Constant-Round Coloring in the Congested Clique.”https://doi.org/10.1145/3382734.3405751__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 .
LibreCat: https://research-explorer.ista.ac.at/record/7803
DOI: 10.1145/3382734.3405751
arXiv: 2009.06043

Aksenov, Vitaly, Dan-Adrian Alistarh, Alexandra Drozdova, and Amirkeivan Mohtashami. “The Splay-List: A Distribution-Adaptive Concurrent Skip-List.”https://doi.org/10.4230/LIPIcs.DISC.2020.3__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 .
LibreCat: https://research-explorer.ista.ac.at/record/8725
DOI: 10.4230/LIPIcs.DISC.2020.3
arXiv: 2008.01009

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.
LibreCat: https://research-explorer.ista.ac.at/record/9632
arXiv: 2004.14340

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.
LibreCat: https://research-explorer.ista.ac.at/record/9631
arXiv: 2002.11505

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.
LibreCat: https://research-explorer.ista.ac.at/record/9415

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.”https://doi.org/10.1109/TSP.2020.3010355__IEEE Transactions on Signal Processing. IEEE, 2020.https://doi.org/10.1109/TSP.2020.3010355 .
LibreCat: https://research-explorer.ista.ac.at/record/8268
DOI: 10.1109/TSP.2020.3010355
WoS: 000562044500001
arXiv: 1802.04907

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.”https://doi.org/10.1145/3332466.3374528__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 .
LibreCat: https://research-explorer.ista.ac.at/record/8722
DOI: 10.1145/3332466.3374528
WoS: 000564476500004
arXiv: 1908.04207

Rybicki, Joel, Nerea Abrego, and Otso Ovaskainen. “Habitat Fragmentation and Species Diversity in Competitive Communities.”https://doi.org/10.1111/ele.13450__Ecology Letters. Wiley, 2020.https://doi.org/10.1111/ele.13450 .
LibreCat: https://research-explorer.ista.ac.at/record/7224
DOI: 10.1111/ele.13450
WoS: 000503625200001

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.
LibreCat: https://research-explorer.ista.ac.at/record/8724
arXiv: 2002.10384

Bhatia, Sumit, Bapi Chatterjee, Deepak Nathani, and Manohar Kaul. “A Persistent Homology Perspective to the Link Prediction Problem.”https://doi.org/10.1007/978-3-030-36687-2_3__In Complex Networks and Their Applications VIII, 881:27–39. Springer Nature, 2020.https://doi.org/10.1007/978-3-030-36687-2_3 .
LibreCat: https://research-explorer.ista.ac.at/record/7213
DOI: 10.1007/978-3-030-36687-2_3
WoS: 000843927300003

Czumaj, Artur, Peter Davies, and Merav Parter. “Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space.”https://doi.org/10.1145/3350755.3400282__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 .
LibreCat: https://research-explorer.ista.ac.at/record/7802
DOI: 10.1145/3350755.3400282
WoS: 000744436200015
arXiv: 1912.05390

Brown, Trevor A, Aleksandar Prokopec, and Dan-Adrian Alistarh. “Non-Blocking Interpolation Search Trees with Doubly-Logarithmic Running Time.”https://doi.org/10.1145/3332466.3374542__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 .
LibreCat: https://research-explorer.ista.ac.at/record/7636
DOI: 10.1145/3332466.3374542
WoS: 000564476500020

Alistarh, Dan-Adrian, Trevor A Brown, and Nandini Singhal. “Memory Tagging: Minimalist Synchronization for Scalable Concurrent Data Structures.”https://doi.org/10.1145/3350755.3400213__In Annual ACM Symposium on Parallelism in Algorithms and Architectures, 37–49. Association for Computing Machinery, 2020.https://doi.org/10.1145/3350755.3400213 .
LibreCat: https://research-explorer.ista.ac.at/record/8191
DOI: 10.1145/3350755.3400213
WoS: 000744436200004