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158 Publications

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: 19518 | OA
Wu D, Modoranu I-V, Safaryan M, Kuznedelev D, Alistarh D-A. 2024. The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 19510 | OA
Modoranu I-V, Safaryan M, Malinovsky G, Kurtic E, Robert T, Richtárik P, Alistarh D-A. 2024. MICROADAM: Accurate adaptive optimization with low space overhead and provable convergence. 38th Conference on Neural Information Processing Systems. , Advances in Neural Information Processing Systems, vol. 37.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 19511 | OA
Ashkboos S, Mohtashami A, Croci ML, Li B, Cameron P, Jaggi M, Alistarh D-A, Hoefler T, Hensman J. 2024. QuaRot: Outlier-free 4-bit inference in rotated LLMs. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2024 | Published | Conference Paper | IST-REx-ID: 19519 | OA
Malinovskii V, Mazur D, Ilin I, Kuznedelev D, Burlachenko K, Yi K, Alistarh D-A, Richtarik P. 2024. PV-tuning: Beyond straight-through estimation for extreme LLM compression. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.
[Published Version] View | Files available | arXiv
 
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.) | WoS | 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 | WoS
 
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 | Research Data Reference | IST-REx-ID: 19884 | OA
Frantar E, Castro R, Chen J, Hoefler T, Alistarh D-A. 2024. MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models, Zenodo, 10.5281/ZENODO.14213091.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2024 | Published | Thesis | IST-REx-ID: 17465 | OA
Shevchenko A. 2024. High-dimensional limits in artificial neural networks. Institute of Science and Technology Austria.
[Published Version] View | Files available | DOI
 
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
 
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: 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: 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: 14815 | OA
Beznosikov A, Horvath S, Richtarik P, Safaryan M. 2023. On biased compression for distributed learning. Journal of Machine Learning Research. 24, 1–50.
[Published Version] View | Files available | 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 | Conference Paper | IST-REx-ID: 17378 | OA
Frantar E, Ashkboos S, Hoefler T, Alistarh D-A. 2023. OPTQ: Accurate post-training quantization for generative pre-trained transformers. 11th International Conference on Learning Representations . ICLR: International Conference on Learning Representations.
[Published Version] View | Files available
 
2023 | Published | Conference Paper | IST-REx-ID: 14458 | OA
Frantar E, Alistarh D-A. 2023. SparseGPT: Massive language models can be accurately pruned in one-shot. Proceedings of the 40th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 202, 10323–10337.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
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
 

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