article · Nature · 2022
Discovering faster matrix multiplication algorithms with reinforcement learning
Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera‐Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Świrszcz, David Silver, Demis Hassabis, Pushmeet Kohli
Cited by 426Open access
Abstract
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Cite this paper
Fawzi, A., Balog, M., Huang, A., Hubert, T., Romera‐Paredes, B., Barekatain, M., Novikov, A., Ruiz, F. J. R., Schrittwieser, J., Świrszcz, G., Silver, D., Hassabis, D., & Kohli, P. (2022). Discovering faster matrix multiplication algorithms with reinforcement learning. Nature, 610(7930), 47–53. https://doi.org/10.1038/s41586-022-05172-4
Fawzi, Alhussein, et al. “Discovering faster matrix multiplication algorithms with reinforcement learning.” Nature, vol. 610, no. 7930, 2022, pp. 47–53, https://doi.org/10.1038/s41586-022-05172-4.
Fawzi, Alhussein, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera‐Paredes, Mohammadamin Barekatain, Alexander Novikov, et al. 2022. “Discovering faster matrix multiplication algorithms with reinforcement learning.” Nature 610 (7930): 47–53. https://doi.org/10.1038/s41586-022-05172-4.
Fawzi, A. et al. (2022) ‘Discovering faster matrix multiplication algorithms with reinforcement learning’, Nature, 610(7930), pp. 47–53. Available at: https://doi.org/10.1038/s41586-022-05172-4.
@article{fawzi2022discovering,
title = {{Discovering faster matrix multiplication algorithms with reinforcement learning}},
author = {Fawzi, Alhussein and Balog, Matej and Huang, Aja and Hubert, Thomas and Romera‐Paredes, Bernardino and Barekatain, Mohammadamin and Novikov, Alexander and Ruiz, Francisco J. R. and Schrittwieser, Julian and Świrszcz, Grzegorz and Silver, David and Hassabis, Demis and Kohli, Pushmeet},
journal = {Nature},
volume = {610},
number = {7930},
pages = {47--53},
year = {2022},
doi = {10.1038/s41586-022-05172-4}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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