Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
138 Publications
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.
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.
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| 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).
[Published Version]
View
| Files available
| DOI
N. Koval, D. Khalanskiy, D.-A. Alistarh, Proceedings of the ACM on Programming Languages 7 (2023).
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| 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| Conference Paper | IST-REx-ID: 14460 |
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
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.
2023 |Published| Journal Article | IST-REx-ID: 14364 |
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
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, L. Zhu, SIAM Journal on Computing 52 (2023) 913–944.
2023 |Published| Conference Paper | IST-REx-ID: 14771 |
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
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.
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.
[Published Version]
View
| Files available
| WoS
| arXiv
A. Beznosikov, S. Horvath, P. Richtarik, M. Safaryan, Journal of Machine Learning Research 24 (2023) 1–50.
2023 |Published| Conference Paper | IST-REx-ID: 14260 |
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
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.
2023 | Research Data Reference | IST-REx-ID: 14995 |
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.)
N. Koval, A. Fedorov, M. Sokolova, D. Tsitelov, D.-A. Alistarh, (2023).
2023 |Published| Conference Paper | IST-REx-ID: 13262 |
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
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.
2023 |Published| Conference Paper | IST-REx-ID: 15363 |
Knowledge distillation performs partial variance reduction
M. Safaryan, A. Krumes, D.-A. Alistarh, in:, 36th Conference on Neural Information Processing Systems, 2023.
[Published Version]
View
| Files available
| arXiv
M. Safaryan, A. Krumes, D.-A. Alistarh, in:, 36th Conference on Neural Information Processing Systems, 2023.
2023 |Published| Thesis | IST-REx-ID: 13074 |
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
E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute of Science and Technology Austria, 2023.
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.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
A. Krumes, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , OpenReview, 2023.
2023 |Published| Conference Paper | IST-REx-ID: 14459 |
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
| Files available
| Download Preprint (ext.)
| arXiv
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.
2023 |Published| Conference Paper | IST-REx-ID: 14461 |
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
| Files available
| Download Preprint (ext.)
| arXiv
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.
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| Conference Paper | IST-REx-ID: 14458 |
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
| Files available
| Download Preprint (ext.)
| arXiv
E. Frantar, D.-A. Alistarh, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 10323–10337.
2022 |Published| Conference Paper | IST-REx-ID: 11184 |
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
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.
2022 |Published| Conference Paper | IST-REx-ID: 11183 |
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
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.
2022 |Published| Conference Paper | IST-REx-ID: 12182 |
Brief announcement: Temporal locality in online algorithms
M. Pacut, M. Parham, J. Rybicki, S. Schmid, J. Suomela, A. Tereshchenko, in:, 36th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
[Published Version]
View
| Files available
| DOI
M. Pacut, M. Parham, J. Rybicki, S. Schmid, J. Suomela, A. Tereshchenko, in:, 36th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
2022 |Published| Conference Paper | IST-REx-ID: 11844 |
Near-optimal leader election in population protocols on graphs
D.-A. Alistarh, J. Rybicki, S. Voitovych, in:, Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2022, pp. 246–256.
[Published Version]
View
| Files available
| DOI
| arXiv
D.-A. Alistarh, J. Rybicki, S. Voitovych, in:, Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2022, pp. 246–256.
2022 |Published| Conference Paper | IST-REx-ID: 11181 |
PathCAS: An efficient middle ground for concurrent search data structures
T.A. Brown, W. Sigouin, D.-A. Alistarh, in:, Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 385–399.
[Published Version]
View
| Files available
| DOI
| WoS
T.A. Brown, W. Sigouin, D.-A. Alistarh, in:, Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 385–399.
2022 |Published| Conference Paper | IST-REx-ID: 11180 |
Multi-queues can be state-of-the-art priority schedulers
A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 353–367.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, in:, Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2022, pp. 353–367.
2022 | Research Data Reference | IST-REx-ID: 13076 |
Multi-queues can be state-of-the-art priority schedulers
A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, (2022).
[Published Version]
View
| Files available
| DOI
| Download Published Version (ext.)
A. Postnikova, N. Koval, G. Nadiradze, D.-A. Alistarh, (2022).
2022 |Published| Conference Paper | IST-REx-ID: 11707 |
Local mending
A. Balliu, J. Hirvonen, D. Melnyk, D. Olivetti, J. Rybicki, J. Suomela, in:, M. Parter (Ed.), International Colloquium on Structural Information and Communication Complexity, Springer Nature, 2022, pp. 1–20.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
A. Balliu, J. Hirvonen, D. Melnyk, D. Olivetti, J. Rybicki, J. Suomela, in:, M. Parter (Ed.), International Colloquium on Structural Information and Communication Complexity, Springer Nature, 2022, pp. 1–20.
2022 |Published| Conference Paper | IST-REx-ID: 12299 |
How well do sparse ImageNet models transfer?
E.B. Iofinova, E.-A. Peste, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–12266.
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| WoS
| arXiv
E.B. Iofinova, E.-A. Peste, M. Kurtz, D.-A. Alistarh, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 12256–12266.
2022 |Published| Journal Article | IST-REx-ID: 8286 |
Dynamic averaging load balancing on cycles
D.-A. Alistarh, G. Nadiradze, A. Sabour, Algorithmica 84 (2022) 1007–1029.
[Published Version]
View
| Files available
| DOI
| WoS
| arXiv
D.-A. Alistarh, G. Nadiradze, A. Sabour, Algorithmica 84 (2022) 1007–1029.
2022 |Published| Conference Paper | IST-REx-ID: 17088 |
The optimal BERT surgeon: Scalable and accurate second-order pruning for large language models
E. Kurtic, D. Campos, T. Nguyen, E. Frantar, M. Kurtz, B. Fineran, M. Goin, D.-A. Alistarh, in:, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2022, pp. 4163–4181.
[Published Version]
View
| Files available
| DOI
| arXiv
E. Kurtic, D. Campos, T. Nguyen, E. Frantar, M. Kurtz, B. Fineran, M. Goin, D.-A. Alistarh, in:, Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2022, pp. 4163–4181.
2022 |Published| Conference Paper | IST-REx-ID: 17059 |
SPDY: Accurate pruning with speedup guarantees
E. Frantar, D.-A. Alistarh, in:, 39th International Conference on Machine Learning, ML Research Press, 2022, pp. 6726–6743.
[Published Version]
View
| Files available
| WoS
E. Frantar, D.-A. Alistarh, in:, 39th International Conference on Machine Learning, ML Research Press, 2022, pp. 6726–6743.
2022 |Published| Journal Article | IST-REx-ID: 11420 |
Mean-field analysis of piecewise linear solutions for wide ReLU networks
A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.
[Published Version]
View
| Files available
| arXiv
A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research 23 (2022) 1–55.
2022 |Published| Conference Paper | IST-REx-ID: 12780 |
CGX: Adaptive system support for communication-efficient deep learning
I. Markov, H. Ramezanikebrya, D.-A. Alistarh, in:, Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–254.
[Published Version]
View
| Files available
| DOI
| arXiv
I. Markov, H. Ramezanikebrya, D.-A. Alistarh, in:, Proceedings of the 23rd ACM/IFIP International Middleware Conference, Association for Computing Machinery, 2022, pp. 241–254.
2022 |Published| Conference Paper | IST-REx-ID: 17087 |
Optimal brain compression: A framework for accurate post-training quantization and pruning
E. Frantar, S.P. Singh, D.-A. Alistarh, in:, 36th Conference on Neural Information Processing Systems, ML Research Press, 2022.
[Submitted Version]
View
| Files available
| arXiv
E. Frantar, S.P. Singh, D.-A. Alistarh, in:, 36th Conference on Neural Information Processing Systems, ML Research Press, 2022.
2021 |Published| Journal Article | IST-REx-ID: 10180 |
Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks
T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, E.-A. Peste, Journal of Machine Learning Research 22 (2021) 1–124.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
T. Hoefler, D.-A. Alistarh, T. Ben-Nun, N. Dryden, E.-A. Peste, Journal of Machine Learning Research 22 (2021) 1–124.
2021 |Published| Conference Paper | IST-REx-ID: 10218 |
Brief announcement: Fast graphical population protocols
D.-A. Alistarh, R. Gelashvili, J. Rybicki, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021.
[Published Version]
View
| Files available
| DOI
| arXiv
D.-A. Alistarh, R. Gelashvili, J. Rybicki, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021.
2021 |Published| Conference Paper | IST-REx-ID: 10217 |
Lower bounds for shared-memory leader election under bounded write contention
D.-A. Alistarh, R. Gelashvili, G. Nadiradze, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
[Published Version]
View
| Files available
| DOI
D.-A. Alistarh, R. Gelashvili, G. Nadiradze, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
2021 |Published| Conference Paper | IST-REx-ID: 10216 |
Brief announcement: Non-blocking dynamic unbounded graphs with worst-case amortized bounds
B. Chatterjee, S. Peri, M. Sa, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
[Published Version]
View
| Files available
| DOI
| arXiv
B. Chatterjee, S. Peri, M. Sa, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
2021 |Published| Conference Paper | IST-REx-ID: 10219 |
Brief announcement: Sinkless orientation is hard also in the supported LOCAL model
J. Korhonen, A. Paz, J. Rybicki, S. Schmid, J. Suomela, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
[Published Version]
View
| Files available
| DOI
| arXiv
J. Korhonen, A. Paz, J. Rybicki, S. Schmid, J. Suomela, in:, 35th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021.
2021 |Published| Conference Paper | IST-REx-ID: 10853 |
A scalable concurrent algorithm for dynamic connectivity
A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2021, pp. 208–220.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2021, pp. 208–220.
2021 |Published| Conference Paper | IST-REx-ID: 11436 |
Asynchronous optimization methods for efficient training of deep neural networks with guarantees
V. Kungurtsev, M. Egan, B. Chatterjee, D.-A. Alistarh, in:, 35th AAAI Conference on Artificial Intelligence, AAAI 2021, AAAI Press, 2021, pp. 8209–8216.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
V. Kungurtsev, M. Egan, B. Chatterjee, D.-A. Alistarh, in:, 35th AAAI Conference on Artificial Intelligence, AAAI 2021, AAAI Press, 2021, pp. 8209–8216.
2021 |Published| Conference Paper | IST-REx-ID: 11452 |
Distributed principal component analysis with limited communication
F. Alimisis, P. Davies, B. Vandereycken, D.-A. Alistarh, in:, Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 2823–2834.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
F. Alimisis, P. Davies, B. Vandereycken, D.-A. Alistarh, in:, Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 2823–2834.
2021 |Published| Conference Paper | IST-REx-ID: 11463 |
M-FAC: Efficient matrix-free approximations of second-order information
E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 14873–14886.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 14873–14886.
2021 |Published| Conference Paper | IST-REx-ID: 11464 |
Towards tight communication lower bounds for distributed optimisation
D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 7254–7266.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 7254–7266.
2021 |Published| Conference Paper | IST-REx-ID: 9543 |
New bounds for distributed mean estimation and variance reduction
P. Davies, V. Gurunanthan, N. Moshrefi, S. Ashkboos, D.-A. Alistarh, in:, 9th International Conference on Learning Representations, 2021.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
P. Davies, V. Gurunanthan, N. Moshrefi, S. Ashkboos, D.-A. Alistarh, in:, 9th International Conference on Learning Representations, 2021.
2021 |Published| Conference Paper | IST-REx-ID: 9620 |
Collecting coupons is faster with friends
D.-A. Alistarh, P. Davies, in:, Structural Information and Communication Complexity, Springer Nature, 2021, pp. 3–12.
[Preprint]
View
| Files available
| DOI
D.-A. Alistarh, P. Davies, in:, Structural Information and Communication Complexity, Springer Nature, 2021, pp. 3–12.
2021 |Published| Conference Paper | IST-REx-ID: 9823 |
Wait-free approximate agreement on graphs
D.-A. Alistarh, F. Ellen, J. Rybicki, in:, Structural Information and Communication Complexity, Springer Nature, 2021, pp. 87–105.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
D.-A. Alistarh, F. Ellen, J. Rybicki, in:, Structural Information and Communication Complexity, Springer Nature, 2021, pp. 87–105.
2021 |Published| Conference Paper | IST-REx-ID: 11458 |
AC/DC: Alternating Compressed/DeCompressed training of deep neural networks
E.-A. Peste, E.B. Iofinova, A. Vladu, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 8557–8570.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
E.-A. Peste, E.B. Iofinova, A. Vladu, D.-A. Alistarh, in:, 35th Conference on Neural Information Processing Systems, Curran Associates, 2021, pp. 8557–8570.