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138 Publications


2024 |Published| Conference Paper | IST-REx-ID: 15011 | OA
Kurtic E, Hoefler T, Alistarh D-A. 2024. How to prune your language model: Recovering accuracy on the ‘Sparsity May Cry’ benchmark. Proceedings of Machine Learning Research. CPAL: Conference on Parsimony and Learning, PMLR, vol. 234, 542–553.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 |Published| Conference Paper | IST-REx-ID: 17093 | OA
Zakerinia H, Talaei S, Nadiradze G, Alistarh D-A. 2024. Communication-efficient federated learning with data and client heterogeneity. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 238, 3448–3456.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2024 |Published| Conference Paper | IST-REx-ID: 17329 | OA
Alistarh D-A, Chatterjee K, Karrabi M, Lazarsfeld JM. 2024. Game dynamics and equilibrium computation in the population protocol model. Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing. PODC: Symposium on Principles of Distributed Computing, 40–49.
[Published Version] View | Files available | DOI
 

2024 |Published| Conference Paper | IST-REx-ID: 17332 | OA
Kokorin I, Yudov V, Aksenov V, Alistarh D-A. 2024. Wait-free trees with asymptotically-efficient range queries. 2024 IEEE International Parallel and Distributed Processing Symposium. IPDPS: International Parallel and Distributed Processing Symposium, 169–179.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2024 |Published| Conference Paper | IST-REx-ID: 17469 | OA
Kögler K, Shevchenko A, Hassani H, Mondelli M. 2024. Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth. Proceedings of the 41st International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 235, 24964–25015.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2024 |Published| Thesis | IST-REx-ID: 17465
Shevchenko A. 2024. High-dimensional limits in artificial neural networks. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 

2024 |Published| Thesis | IST-REx-ID: 17490 | OA
Markov I. 2024. Communication-efficient distributed training of deep neural networks: An algorithms and systems perspective. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 

2024 |Published| Conference Paper | IST-REx-ID: 17456 | OA
Markov I, Alimohammadi K, Frantar E, Alistarh D-A. 2024. L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning. Proceedings of Machine Learning and Systems . MLSys: Machine Learning and Systems vol. 6.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2024 |Published| Conference Paper | IST-REx-ID: 18070
Chatterjee B, Kungurtsev V, Alistarh D-A. 2024. Federated SGD with local asynchrony. Proceedings of the 44th International Conference on Distributed Computing Systems. ICDCS: International Conference on Distributed Computing Systems, 857–868.
View | DOI
 

2024 |Published| Thesis | IST-REx-ID: 17485 | OA
Frantar E. 2024. Compressing large neural networks : Algorithms, systems and scaling laws. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 

2024 |Published| Conference Paper | IST-REx-ID: 18061 | OA
Frantar E, Alistarh D-A. 2024. QMoE: Sub-1-bit compression of trillion parameter models. Proceedings of Machine Learning and Systems. MLSys: Machine Learning and Systems vol. 6.
[Published Version] View | Files available | Download Published Version (ext.)
 

2024 |Published| Conference Paper | IST-REx-ID: 18062 | OA
Frantar E, Ruiz CR, Houlsby N, Alistarh D-A, Evci U. 2024. Scaling laws for sparsely-connected foundation models. The Twelfth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

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

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

2023 |Published| Journal Article | IST-REx-ID: 13179 | OA
Koval N, Khalanskiy D, Alistarh D-A. 2023. CQS: A formally-verified framework for fair and abortable synchronization. Proceedings of the ACM on Programming Languages. 7, 116.
[Published Version] View | Files available | DOI
 

2023 |Published| Journal Article | IST-REx-ID: 12566 | OA
Alistarh D-A, Ellen F, Rybicki J. 2023. Wait-free approximate agreement on graphs. Theoretical Computer Science. 948(2), 113733.
[Published Version] View | Files available | DOI | WoS
 

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

2023 |Published| Conference Paper | IST-REx-ID: 14460 | OA
Nikdan M, Pegolotti T, Iofinova EB, Kurtic E, Alistarh D-A. 2023. SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 26215–26227.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 |Published| Journal Article | IST-REx-ID: 14364 | OA
Alistarh D-A, Aspnes J, Ellen F, Gelashvili R, Zhu L. 2023. Why extension-based proofs fail. SIAM Journal on Computing. 52(4), 913–944.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

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

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