論文

• Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota. Scalable and Practical Natural Gradient for Large-Scale Deep Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, June 2020.

国際会議発表 (査読有り)

• Yuichiro Ueno, Kazuki Osawa, Yohei Tsuji, Akira Naruse, Rio Yokota. Rich Information is Affordable: A Systematic Performance Analysis of Second-order Optimization Using K-FAC, 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Aug. 2021.
• Rio Yokota, Yohei Tsuji, Kazuki Osawa. Second Order Optimization for Distributed Data-parallel Deep Learning on 4000 GPUs, I2R-TokyoTech Co-workshop on DL 2.0, Mar. 2020.
• Yohei Tsuji, Kazuki Osawa, Yuichiro Ueno, Akira Naruse, Rio Yokota, Satoshi Matsuoka. Performance Optimizations and Analysis of Distributed Deep Learning with Approximated Second-Order Optimization Method, International Conference on Parallel Processing: The 1st Workshop on Parallel and Distributed Machine Learning, Proceedings of the 48th International Conference on Parallel Processing: Workshops, No. 21, Aug. 2019.
• Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Rio Yokota, Satoshi Matsuoka. Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs, IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 2019.

国内会議発表 (査読なし・不明)

• 横田理央, 大沢和樹, 辻陽平, 上野裕一郎, 成瀬彰. 大規模並列深層学習における2次の最適化手法の効果, 電子情報通信学会総合大会, Mar. 2019.
• 辻 陽平, 野村 哲弘, 實本 英之, 佐藤 育郎, 松岡 聡. 動的なプロセス数操作による分散深層学習の耐故障性と性能評価, 情報処理学会研究報告 IPSJ SIG Technical Report, July 2017.

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