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115 Publications


2024 | Conference Paper | IST-REx-ID: 15011 | OA
How to prune your language model: Recovering accuracy on the "Sparsity May Cry" benchmark
E. Kurtic, T. Hoefler, D.-A. Alistarh, in:, Proceedings of Machine Learning Research, ML Research Press, 2024, pp. 542–553.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 12735 | OA
Fast and scalable channels in Kotlin Coroutines
N. Koval, D.-A. Alistarh, R. Elizarov, in:, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2023, pp. 107–118.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Poster | IST-REx-ID: 12736 | OA
Unexpected scaling in path copying trees
V. Aksenov, T.A. Brown, A. Fedorov, I. Kokorin, Unexpected Scaling in Path Copying Trees, Association for Computing Machinery, 2023.
[Published Version] View | DOI | Download Published Version (ext.)
 

2023 | Conference Paper | IST-REx-ID: 13053 | OA
CrAM: A Compression-Aware Minimizer
E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, 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
CQS: A formally-verified framework for fair and abortable synchronization
N. Koval, D. Khalanskiy, D.-A. Alistarh, Proceedings of the ACM on Programming Languages 7 (2023).
[Published Version] View | Files available | DOI
 

2023 | Conference Paper | IST-REx-ID: 13262 | OA
Provably-efficient and internally-deterministic parallel Union-Find
A. Fedorov, D. Hashemi, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2023, pp. 261–271.
[Published Version] View | Files available | DOI | arXiv
 

2023 | Journal Article | IST-REx-ID: 12566 | OA
Wait-free approximate agreement on graphs
D.-A. Alistarh, F. Ellen, J. Rybicki, Theoretical Computer Science 948 (2023).
[Published Version] View | Files available | DOI | WoS
 

2023 | Thesis | IST-REx-ID: 13074 | OA
Efficiency and generalization of sparse neural networks
E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
[Published Version] View | Files available | DOI
 

2023 | Journal Article | IST-REx-ID: 12330 | OA
The splay-list: A distribution-adaptive concurrent skip-list
V. Aksenov, D.-A. Alistarh, A. Drozdova, A. Mohtashami, Distributed Computing 36 (2023) 395–418.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14461 | OA
Quantized distributed training of large models with convergence guarantees
I. Markov, A. Vladu, Q. Guo, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 24020–24044.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14459 | OA
Fundamental limits of two-layer autoencoders, and achieving them with gradient methods
A. Shevchenko, K. Kögler, H. Hassani, M. Mondelli, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 31151–31209.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14460 | OA
SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge
M. Nikdan, T. Pegolotti, E.B. Iofinova, E. Kurtic, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 26215–26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14458 | OA
SparseGPT: Massive language models can be accurately pruned in one-shot
E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 14364 | OA
Why extension-based proofs fail
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, L. Zhu, SIAM Journal on Computing 52 (2023) 913–944.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14771 | OA
Bias in pruned vision models: In-depth analysis and countermeasures
E.B. Iofinova, E.-A. Peste, D.-A. Alistarh, in:, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–24373.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2023 | Journal Article | IST-REx-ID: 14815 | OA
On biased compression for distributed learning
A. Beznosikov, S. Horvath, P. Richtarik, M. Safaryan, Journal of Machine Learning Research 24 (2023) 1–50.
[Published Version] View | Files available | WoS | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14260 | OA
Lincheck: A practical framework for testing concurrent data structures on JVM
N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, D.-A. Alistarh, in:, 35th International Conference on Computer Aided Verification , Springer Nature, 2023, pp. 156–169.
[Published Version] View | Files available | DOI
 

2023 | Research Data Reference | IST-REx-ID: 14995 | OA
Lincheck: A practical framework for testing concurrent data structures on JVM
N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, D.-A. Alistarh, (2023).
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

2022 | Conference Paper | IST-REx-ID: 11184 | OA
Fast graphical population protocols
D.-A. Alistarh, R. Gelashvili, J. Rybicki, in:, Q. Bramas, V. Gramoli, A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
[Published Version] View | Files available | DOI | arXiv
 

2022 | Conference Paper | IST-REx-ID: 11183 | OA
Beyond distributed subgraph detection: Induced subgraphs, multicolored problems and graph parameters
A. Nikabadi, J. Korhonen, in:, Q. Bramas, V. Gramoli, A. Milani (Eds.), 25th International Conference on Principles of Distributed Systems, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
[Published Version] View | Files available | DOI
 

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