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141 Publications
2024 | Published | Thesis | IST-REx-ID: 17485 | 
Compressing large neural networks : Algorithms, systems and scaling laws
E. Frantar, Compressing Large Neural Networks : Algorithms, Systems and Scaling Laws, Institute of Science and Technology Austria, 2024.
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E. Frantar, Compressing Large Neural Networks : Algorithms, Systems and Scaling Laws, Institute of Science and Technology Austria, 2024.
2024 | Published | Conference Paper | IST-REx-ID: 18061 |
QMoE: Sub-1-bit compression of trillion parameter models
E. Frantar, D.-A. Alistarh, in:, P. Gibbons, G. Pekhimenko, C. De Sa (Eds.), Proceedings of Machine Learning and Systems, 2024.
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E. Frantar, D.-A. Alistarh, in:, P. Gibbons, G. Pekhimenko, C. De Sa (Eds.), Proceedings of Machine Learning and Systems, 2024.
2024 | Published | Conference Paper | IST-REx-ID: 18062 |
Scaling laws for sparsely-connected foundation models
E. Frantar, C.R. Ruiz, N. Houlsby, D.-A. Alistarh, U. Evci, in:, The Twelfth International Conference on Learning Representations, 2024.
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E. Frantar, C.R. Ruiz, N. Houlsby, D.-A. Alistarh, U. Evci, in:, The Twelfth International Conference on Learning Representations, 2024.
2024 | Published | Conference Paper | IST-REx-ID: 18070
Federated SGD with local asynchrony
B. Chatterjee, V. Kungurtsev, D.-A. Alistarh, in:, Proceedings of the 44th International Conference on Distributed Computing Systems, IEEE, 2024, pp. 857–868.
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B. Chatterjee, V. Kungurtsev, D.-A. Alistarh, in:, Proceedings of the 44th International Conference on Distributed Computing Systems, IEEE, 2024, pp. 857–868.
2024 | Published | Conference Paper | IST-REx-ID: 18113 |
Extreme compression of large language models via additive quantization
V. Egiazarian, A. Panferov, D. Kuznedelev, E. Frantar, A. Babenko, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 12284–12303.
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V. Egiazarian, A. Panferov, D. Kuznedelev, E. Frantar, A. Babenko, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 12284–12303.
2024 | Published | Conference Paper | IST-REx-ID: 18117 |
RoSA: Accurate parameter-efficient fine-tuning via robust adaptation
M. Nikdan, S. Tabesh, E. Crncevic, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 38187–38206.
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M. Nikdan, S. Tabesh, E. Crncevic, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 38187–38206.
2024 | Published | Conference Paper | IST-REx-ID: 18121 |
SPADE: Sparsity-guided debugging for deep neural networks
A.S. Moakhar, E.B. Iofinova, E. Frantar, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 45955–45987.
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A.S. Moakhar, E.B. Iofinova, E. Frantar, D.-A. Alistarh, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 45955–45987.
2024 | Published | Conference Paper | IST-REx-ID: 15011 |
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.
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E. Kurtic, T. Hoefler, D.-A. Alistarh, in:, Proceedings of Machine Learning Research, ML Research Press, 2024, pp. 542–553.
2024 | Published | Conference Paper | IST-REx-ID: 17469 |
Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth
K. Kögler, A. Shevchenko, H. Hassani, M. Mondelli, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 24964–25015.
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K. Kögler, A. Shevchenko, H. Hassani, M. Mondelli, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 24964–25015.
2024 | Published | Thesis | IST-REx-ID: 17465 |
High-dimensional limits in artificial neural networks
A. Shevchenko, High-Dimensional Limits in Artificial Neural Networks, Institute of Science and Technology Austria, 2024.
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A. Shevchenko, High-Dimensional Limits in Artificial Neural Networks, Institute of Science and Technology Austria, 2024.
2023 | Published | Conference Poster | IST-REx-ID: 12736 |
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.
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V. Aksenov, T.A. Brown, A. Fedorov, I. Kokorin, Unexpected Scaling in Path Copying Trees, Association for Computing Machinery, 2023.
2023 | Published | Conference Paper | IST-REx-ID: 17378 |
OPTQ: Accurate post-training quantization for generative pre-trained transformers
E. Frantar, S. Ashkboos, T. Hoefler, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , International Conference on Learning Representations, 2023.
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E. Frantar, S. Ashkboos, T. Hoefler, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , International Conference on Learning Representations, 2023.
2023 | Published | Journal Article | IST-REx-ID: 12330 |
The splay-list: A distribution-adaptive concurrent skip-list
V. Aksenov, D.-A. Alistarh, A. Drozdova, A. Mohtashami, Distributed Computing 36 (2023) 395–418.
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V. Aksenov, D.-A. Alistarh, A. Drozdova, A. Mohtashami, Distributed Computing 36 (2023) 395–418.
2023 | Published | Journal Article | IST-REx-ID: 12566 |
Wait-free approximate agreement on graphs
D.-A. Alistarh, F. Ellen, J. Rybicki, Theoretical Computer Science 948 (2023).
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D.-A. Alistarh, F. Ellen, J. Rybicki, Theoretical Computer Science 948 (2023).
2023 | Published | Conference Paper | IST-REx-ID: 12735 |
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.
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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.
2023 | Published | Conference Paper | IST-REx-ID: 13053 |
CrAM: A Compression-Aware Minimizer
A. Krumes, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , OpenReview, 2023.
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A. Krumes, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , OpenReview, 2023.
2023 | Published | Thesis | IST-REx-ID: 13074 |
Efficiency and generalization of sparse neural networks
A. Krumes, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
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A. Krumes, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
2023 | Published | Journal Article | IST-REx-ID: 13179 |
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).
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N. Koval, D. Khalanskiy, D.-A. Alistarh, Proceedings of the ACM on Programming Languages 7 (2023).
2023 | Published | Conference Paper | IST-REx-ID: 14771 |
Bias in pruned vision models: In-depth analysis and countermeasures
E.B. Iofinova, A. Krumes, D.-A. Alistarh, in:, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–24373.
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E.B. Iofinova, A. Krumes, D.-A. Alistarh, in:, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 24364–24373.
2023 | Published | Journal Article | IST-REx-ID: 14815 |
On biased compression for distributed learning
A. Beznosikov, S. Horvath, P. Richtarik, M. Safaryan, Journal of Machine Learning Research 24 (2023) 1–50.
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A. Beznosikov, S. Horvath, P. Richtarik, M. Safaryan, Journal of Machine Learning Research 24 (2023) 1–50.