Shevchenko A, Kögler K, Hassani H, Mondelli M. Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:31151-31209.
LibreCat: https://research-explorer.ista.ac.at/record/14459
arXiv: 2212.13468

Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:26215-26227.
LibreCat: https://research-explorer.ista.ac.at/record/14460
arXiv: 2302.04852

Frantar E, Alistarh D-A. SparseGPT: Massive language models can be accurately pruned in one-shot. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:10323-10337.
LibreCat: https://research-explorer.ista.ac.at/record/14458
arXiv: 2301.00774

Alistarh D-A, Aspnes J, Ellen F, Gelashvili R, Zhu L. Why extension-based proofs fail. SIAM Journal on Computing. 2023;52(4):913-944. doi:10.1137/20M1375851
LibreCat: https://research-explorer.ista.ac.at/record/14364
DOI: 10.1137/20M1375851
WoS: 001082972300004
arXiv: 1811.01421

Iofinova EB, Peste E-A, Alistarh D-A. Bias in pruned vision models: In-depth analysis and countermeasures. In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2023:24364-24373. doi:10.1109/cvpr52729.2023.02334
LibreCat: https://research-explorer.ista.ac.at/record/14771
DOI: 10.1109/cvpr52729.2023.02334
WoS: 001062531308068
arXiv: 2304.12622

Beznosikov A, Horvath S, Richtarik P, Safaryan M. On biased compression for distributed learning. Journal of Machine Learning Research. 2023;24:1-50.
LibreCat: https://research-explorer.ista.ac.at/record/14815
WoS: 001111578500001
arXiv: 2002.12410

Koval N, Fedorov A, Sokolova M, Tsitelov D, Alistarh D-A. Lincheck: A practical framework for testing concurrent data structures on JVM. In: 35th International Conference on Computer Aided Verification . Vol 13964. Springer Nature; 2023:156-169. doi:10.1007/978-3-031-37706-8_8
LibreCat: https://research-explorer.ista.ac.at/record/14260
DOI: 10.1007/978-3-031-37706-8_8

Koval N, Fedorov A, Sokolova M, Tsitelov D, Alistarh D-A. Lincheck: A practical framework for testing concurrent data structures on JVM. 2023. doi:10.5281/ZENODO.7877757
LibreCat: https://research-explorer.ista.ac.at/record/14995
DOI: 10.5281/ZENODO.7877757

Fedorov A, Hashemi D, Nadiradze G, Alistarh D-A. Provably-efficient and internally-deterministic parallel Union-Find. In: Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery; 2023:261-271. doi:10.1145/3558481.3591082
LibreCat: https://research-explorer.ista.ac.at/record/13262
DOI: 10.1145/3558481.3591082
arXiv: 2304.09331

Safaryan M, Krumes A, Alistarh D-A. Knowledge distillation performs partial variance reduction. In: 36th Conference on Neural Information Processing Systems. Vol 36. ; 2023.
LibreCat: https://research-explorer.ista.ac.at/record/15363
arXiv: 2305.17581

Alistarh D-A, Gelashvili R, Rybicki J. Fast graphical population protocols. In: Bramas Q, Gramoli V, Milani A, eds. 25th International Conference on Principles of Distributed Systems. Vol 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:10.4230/LIPIcs.OPODIS.2021.14
LibreCat: https://research-explorer.ista.ac.at/record/11184
DOI: 10.4230/LIPIcs.OPODIS.2021.14
arXiv: 2102.08808

Nikabadi A, Korhonen J. Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters. In: Bramas Q, Gramoli V, Milani A, eds. 25th International Conference on Principles of Distributed Systems. Vol 217. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:10.4230/LIPIcs.OPODIS.2021.15
LibreCat: https://research-explorer.ista.ac.at/record/11183
DOI: 10.4230/LIPIcs.OPODIS.2021.15

Shevchenko A, Kungurtsev V, Mondelli M. Mean-field analysis of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning Research. 2022;23(130):1-55.
LibreCat: https://research-explorer.ista.ac.at/record/11420
arXiv: 2111.02278

Pacut M, Parham M, Rybicki J, Schmid S, Suomela J, Tereshchenko A. Brief announcement: Temporal locality in online algorithms. In: 36th International Symposium on Distributed Computing. Vol 246. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:10.4230/LIPIcs.DISC.2022.52
LibreCat: https://research-explorer.ista.ac.at/record/12182
DOI: 10.4230/LIPIcs.DISC.2022.52

Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for communication-efficient deep learning. In: Proceedings of the 23rd ACM/IFIP International Middleware Conference. Association for Computing Machinery; 2022:241-254. doi:10.1145/3528535.3565248
LibreCat: https://research-explorer.ista.ac.at/record/12780
DOI: 10.1145/3528535.3565248
arXiv: 2111.08617

Alistarh D-A, Rybicki J, Voitovych S. Near-optimal leader election in population protocols on graphs. In: Proceedings of the Annual ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2022:246-256. doi:10.1145/3519270.3538435
LibreCat: https://research-explorer.ista.ac.at/record/11844
DOI: 10.1145/3519270.3538435
arXiv: 2205.12597

Brown TA, Sigouin W, Alistarh D-A. 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. Association for Computing Machinery; 2022:385-399. doi:10.1145/3503221.3508410
LibreCat: https://research-explorer.ista.ac.at/record/11181
DOI: 10.1145/3503221.3508410
WoS: 000883318200027

Postnikova A, Koval N, Nadiradze G, Alistarh D-A. 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. Association for Computing Machinery; 2022:353-367. doi:10.1145/3503221.3508432
LibreCat: https://research-explorer.ista.ac.at/record/11180
DOI: 10.1145/3503221.3508432
WoS: 000883318200025
arXiv: 2109.00657

Postnikova A, Koval N, Nadiradze G, Alistarh D-A. Multi-queues can be state-of-the-art priority schedulers. 2022. doi:10.5281/ZENODO.5733408
LibreCat: https://research-explorer.ista.ac.at/record/13076
DOI: 10.5281/ZENODO.5733408

Balliu A, Hirvonen J, Melnyk D, Olivetti D, Rybicki J, Suomela J. Local mending. In: Parter M, ed. International Colloquium on Structural Information and Communication Complexity. Vol 13298. LNCS. Springer Nature; 2022:1-20. doi:10.1007/978-3-031-09993-9_1
LibreCat: https://research-explorer.ista.ac.at/record/11707
DOI: 10.1007/978-3-031-09993-9_1
WoS: 000876977400001
arXiv: 2102.08703