| Large-scale distributed second-order optimization using kronecker-factored approximate curvature for deep convolutional neural networks K Osawa, Y Tsuji, Y Ueno, A Naruse, R Yokota, S Matsuoka Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 156* | 2019 |
| Exhaustive study of hierarchical allreduce patterns for large messages between GPUs Y Ueno, R Yokota 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2019 | 51 | 2019 |
| Scalable and practical natural gradient for large-scale deep learning K Osawa, Y Tsuji, Y Ueno, A Naruse, CS Foo, R Yokota IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (1), 404-415, 2020 | 43 | 2020 |
| Rich information is affordable: A systematic performance analysis of second-order optimization using K-FAC Y Ueno, K Osawa, Y Tsuji, A Naruse, R Yokota Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 20 | 2020 |
| Performance optimizations and analysis of distributed deep learning with approximated second-order optimization method Y Tsuji, K Osawa, Y Ueno, A Naruse, R Yokota, S Matsuoka Workshop Proceedings of the 48th International Conference on Parallel …, 2019 | 7 | 2019 |
Kazuki OsawaGoogle DeepMindE-mailová adresa ověřena na: google.com