Korhonen, Janne, Ami Paz, Joel Rybicki, Stefan Schmid, and Jukka Suomela. “Brief Announcement: Sinkless Orientation Is Hard Also in the Supported LOCAL Model.”https://doi.org/10.4230/LIPIcs.DISC.2021.58__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 .
LibreCat: https://research-explorer.ista.ac.at/record/10219
DOI: 10.4230/LIPIcs.DISC.2021.58
arXiv: 2108.02655

Fedorov, Alexander, Nikita Koval, and Dan-Adrian Alistarh. “A Scalable Concurrent Algorithm for Dynamic Connectivity.”https://doi.org/10.1145/3409964.3461810__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 .
LibreCat: https://research-explorer.ista.ac.at/record/10853
DOI: 10.1145/3409964.3461810
arXiv: 2105.08098

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.
LibreCat: https://research-explorer.ista.ac.at/record/11436
arXiv: 1905.11845

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.
LibreCat: https://research-explorer.ista.ac.at/record/11452
arXiv: 2110.14391

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.
LibreCat: https://research-explorer.ista.ac.at/record/11463
arXiv: 2010.08222

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.
LibreCat: https://research-explorer.ista.ac.at/record/11464
arXiv: 2010.08222

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.
LibreCat: https://research-explorer.ista.ac.at/record/9543
arXiv: 2002.09268

Alistarh, Dan-Adrian, and Peter Davies. “Collecting Coupons Is Faster with Friends.”https://doi.org/10.1007/978-3-030-79527-6_1__In Structural Information and Communication Complexity, 12810:3–12. Springer Nature, 2021.https://doi.org/10.1007/978-3-030-79527-6_1 .
LibreCat: https://research-explorer.ista.ac.at/record/9620
DOI: 10.1007/978-3-030-79527-6_1

Alistarh, Dan-Adrian, Faith Ellen, and Joel Rybicki. “Wait-Free Approximate Agreement on Graphs.”https://doi.org/10.1007/978-3-030-79527-6_6__In Structural Information and Communication Complexity, 12810:87–105. Springer Nature, 2021.https://doi.org/10.1007/978-3-030-79527-6_6 .
LibreCat: https://research-explorer.ista.ac.at/record/9823
DOI: 10.1007/978-3-030-79527-6_6
arXiv: 2103.08949

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.
LibreCat: https://research-explorer.ista.ac.at/record/11458
arXiv: 2106.12379

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.
LibreCat: https://research-explorer.ista.ac.at/record/13147
arXiv: 2102.07214

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.”https://doi.org/10.1109/TPDS.2020.3040606__IEEE Transactions on Parallel and Distributed Systems. IEEE, 2021.https://doi.org/10.1109/TPDS.2020.3040606 .
LibreCat: https://research-explorer.ista.ac.at/record/8723
DOI: 10.1109/TPDS.2020.3040606
WoS: 000621405200019
arXiv: 2005.00124

Chatterjee, Bapi, Ivan Walulya, and Philippas Tsigas. “Concurrent Linearizable Nearest Neighbour Search in LockFree-KD-Tree.”https://doi.org/10.1016/j.tcs.2021.06.041__Theoretical Computer Science. Elsevier, 2021.https://doi.org/10.1016/j.tcs.2021.06.041 .
LibreCat: https://research-explorer.ista.ac.at/record/9827
DOI: 10.1016/j.tcs.2021.06.041
WoS: 000694718900004

Alistarh, Dan-Adrian, Martin Töpfer, and Przemysaw Uznaski. “Comparison Dynamics in Population Protocols.”https://doi.org/10.1145/3465084.3467915__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 .
LibreCat: https://research-explorer.ista.ac.at/record/9951
DOI: 10.1145/3465084.3467915
WoS: 000744439800005

Czumaj, Artur, Peter Davies, and Merav Parter. “Improved Deterministic (+1) Coloring in Low-Space MPC.”https://doi.org/10.1145/3465084.3467937__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 .
LibreCat: https://research-explorer.ista.ac.at/record/9935
DOI: 10.1145/3465084.3467937
WoS: 000744439800048

Czumaj, Artur, Peter Davies, and Merav Parter. “Component Stability in Low-Space Massively Parallel Computation.”https://doi.org/10.1145/3465084.3467903__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 .
LibreCat: https://research-explorer.ista.ac.at/record/9933
DOI: 10.1145/3465084.3467903
WoS: 000744439800049
arXiv: 2106.01880

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.
LibreCat: https://research-explorer.ista.ac.at/record/10432
arXiv: 2001.05918

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.”https://doi.org/10.1109/sp40001.2021.00035__In 2021 IEEE Symposium on Security and Privacy , 268–84. IEEE, 2021.https://doi.org/10.1109/sp40001.2021.00035 .
LibreCat: https://research-explorer.ista.ac.at/record/10049
DOI: 10.1109/sp40001.2021.00035

Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.”https://doi.org/10.1145/3410220.3453923__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 .
LibreCat: https://research-explorer.ista.ac.at/record/10854
DOI: 10.1145/3410220.3453923
arXiv: 2005.07637

Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.”https://doi.org/10.1145/3447384__Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery, 2021.https://doi.org/10.1145/3447384 .
LibreCat: https://research-explorer.ista.ac.at/record/10855
DOI: 10.1145/3447384
arXiv: 2005.07637