Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
141 Publications
2024 | Published | Thesis | IST-REx-ID: 17490 | 
Communication-efficient distributed training of deep neural networks: An algorithms and systems perspective
I. Markov, Communication-Efficient Distributed Training of Deep Neural Networks: An Algorithms and Systems Perspective, Institute of Science and Technology Austria, 2024.
[Published Version]
View
| Files available
| DOI
I. Markov, Communication-Efficient Distributed Training of Deep Neural Networks: An Algorithms and Systems Perspective, Institute of Science and Technology Austria, 2024.
2024 | Published | Conference Paper | IST-REx-ID: 17093 |
Communication-efficient federated learning with data and client heterogeneity
H. Zakerinia, S. Talaei, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2024, pp. 3448–3456.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
H. Zakerinia, S. Talaei, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2024, pp. 3448–3456.
2024 | Published | Conference Paper | IST-REx-ID: 17329 |
Game dynamics and equilibrium computation in the population protocol model
D.-A. Alistarh, K. Chatterjee, M. Karrabi, J.M. Lazarsfeld, in:, Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2024, pp. 40–49.
[Published Version]
View
| Files available
| DOI
D.-A. Alistarh, K. Chatterjee, M. Karrabi, J.M. Lazarsfeld, in:, Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2024, pp. 40–49.
2024 | Published | Conference Paper | IST-REx-ID: 17332 |
Wait-free trees with asymptotically-efficient range queries
I. Kokorin, V. Yudov, V. Aksenov, D.-A. Alistarh, in:, 2024 IEEE International Parallel and Distributed Processing Symposium, IEEE, 2024, pp. 169–179.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
I. Kokorin, V. Yudov, V. Aksenov, D.-A. Alistarh, in:, 2024 IEEE International Parallel and Distributed Processing Symposium, IEEE, 2024, pp. 169–179.
2024 | Published | Conference Paper | IST-REx-ID: 17456 |
L-GreCo: Layerwise-adaptive gradient compression for efficient data-parallel deep learning
I. Markov, K. Alimohammadi, E. Frantar, D.-A. Alistarh, in:, P. Gibbons, G. Pekhimenko, C. De Sa (Eds.), Proceedings of Machine Learning and Systems , Association for Computing Machinery, 2024.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
I. Markov, K. Alimohammadi, E. Frantar, D.-A. Alistarh, in:, P. Gibbons, G. Pekhimenko, C. De Sa (Eds.), Proceedings of Machine Learning and Systems , Association for Computing Machinery, 2024.
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.
[Published Version]
View
| Files available
| DOI
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.
[Published Version]
View
| Files available
| Download Published Version (ext.)
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.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
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.
View
| DOI
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.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
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.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
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.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
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.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
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.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
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.
[Published Version]
View
| Files available
| DOI
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.
[Published Version]
View
| DOI
| Download Published Version (ext.)
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.
[Published Version]
View
| Files available
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.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
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).
[Published Version]
View
| Files available
| DOI
| WoS
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.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
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.