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5069 Publications

2023 | Conference Paper | IST-REx-ID: 14461 | OA
Markov, I., Vladu, A., Guo, Q., & Alistarh, D.-A. (2023). Quantized distributed training of large models with convergence guarantees. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 24020–24044). Honolulu, Hawaii, HI, United States: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14462 | OA
Fichtenberger, H., Henzinger, M. H., & Upadhyay, J. (2023). Constant matters: Fine-grained error bound on differentially private continual observation. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10072–10092). Honolulu, Hawaii, HI, United States: ML Research Press.
[Published Version] View | Download Published Version (ext.)
 
2023 | Conference Paper | IST-REx-ID: 14459 | OA
Shevchenko, A., Kögler, K., Hassani, H., & Mondelli, M. (2023). Fundamental limits of two-layer autoencoders, and achieving them with gradient methods. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 31151–31209). Honolulu, Hawaii, HI, United States: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14460 | OA
Nikdan, M., Pegolotti, T., Iofinova, E. B., Kurtic, E., & Alistarh, D.-A. (2023). SparseProp: Efficient sparse backpropagation for faster training of neural networks at the edge. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 26215–26227). Honolulu, Hawaii, HI, United States: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14457 | OA
Hoffmann, C., & Simkin, M. (2023). Stronger lower bounds for leakage-resilient secret sharing. In 8th International Conference on Cryptology and Information Security in Latin America (Vol. 14168, pp. 215–228). Quito, Ecuador: Springer Nature. https://doi.org/10.1007/978-3-031-44469-2_11
[Preprint] View | DOI | Download Preprint (ext.)
 

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