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8930 Publications


2023 | Journal Article | IST-REx-ID: 14452 | OA
Barton, N. H., Etheridge, A. M., & Véber, A. (2023). The infinitesimal model with dominance. Genetics. Oxford Academic. https://doi.org/10.1093/genetics/iyad133
[Published Version] View | Files available | DOI | arXiv
 

2023 | Research Data | IST-REx-ID: 12949 | OA
Barton, N. H. (2023). The infinitesimal model with dominance. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:12949
[Published Version] View | Files available | DOI
 

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.)
 

2023 | Conference Paper | IST-REx-ID: 14458 | OA
Frantar, E., & Alistarh, D.-A. (2023). SparseGPT: Massive language models can be accurately pruned in one-shot. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 10323–10337). Honolulu, Hawaii, HI, United States: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 14451 | OA
Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2023). Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. Springer Nature. https://doi.org/10.1007/s00521-023-09033-7
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 14442
Rojas Vega, M. N., De Castro, P., & Soto, R. (2023). Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. Springer Nature. https://doi.org/10.1140/epje/s10189-023-00354-y
View | DOI | PubMed | Europe PMC
 

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