Kazuki Osawa

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 24

Top Topics

Convolutional Neural Networks

Graph Databases

Top Venues

Publications

Kazuki Osawa, Satoki Ishikawa, Rio Yokota, Shigang Li, Torsten Hoefler
ASDL: A Unified Interface for Gradient Preconditioning in PyTorch. CoRR (2023)
Erik A. Daxberger, Siddharth Swaroop, Kazuki Osawa, Rio Yokota, Richard E. Turner, José Miguel Hernández-Lobato, Mohammad Emtiyaz Khan
Improving Continual Learning by Accurate Gradient Reconstructions of the Past. Trans. Mach. Learn. Res. 2023 (2023)
Kazuki Osawa, Shigang Li, Torsten Hoefler
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices. MLSys (2023)
Ryo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias. ICML (2023)
Kazuki Osawa, Shigang Li, Torsten Hoefler
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices. CoRR (2022)
Ryo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias. CoRR (2022)
Shigang Li, Kazuki Osawa, Torsten Hoefler
Efficient Quantized Sparse Matrix Operations on Tensor Cores. CoRR (2022)
Maciej Besta, Patrick Iff, Florian Scheidl, Kazuki Osawa, Nikoli Dryden, Michal Podstawski, Tiancheng Chen, Torsten Hoefler
Neural Graph Databases. CoRR (2022)
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
Scalable and Practical Natural Gradient for Large-Scale Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (1) (2022)
Shigang Li, Kazuki Osawa, Torsten Hoefler
Efficient Quantized Sparse Matrix Operations on Tensor Cores. SC (2022)
Maciej Besta, Patrick Iff, Florian Scheidl, Kazuki Osawa, Nikoli Dryden, Michal Podstawski, Tiancheng Chen, Torsten Hoefler
Neural Graph Databases. LoG (2022)
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. KDD (2020)
Keiji Kamei, Masahiro Kaneoka, Ken Yanai, Masaya Umemoto, Hiroki Yamaguchi, Kazuki Osawa
Development of the Image-based Flight and Tree Measurement System in a Forest using a Drone. J. Robotics Netw. Artif. Life 7 (2) (2020)
Ryo Karakida, Kazuki Osawa
Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks. NeurIPS (2020)
Ryo Karakida, Kazuki Osawa
Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks. CoRR (2020)
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
Scalable and Practical Natural Gradient for Large-Scale Deep Learning. CoRR (2020)
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Rio Yokota, Satoshi Matsuoka
Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks. CVPR (2019)
Kazuki Osawa, Siddharth Swaroop, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota, Mohammad Emtiyaz Khan
Practical Deep Learning with Bayesian Principles. CoRR (2019)
Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota
Practical Deep Learning with Bayesian Principles. NeurIPS (2019)
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. ICPP Workshops (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. CoRR (2018)
Kazuki Osawa, Rio Yokota
Evaluating the Compression Efficiency of the Filters in Convolutional Neural Networks. ICANN (2) (2017)
Kazuki Osawa, Akira Sekiya, Hiroki Naganuma, Rio Yokota
Accelerating Matrix Multiplication in Deep Learning by Using Low-Rank Approximation. HPCS (2017)
Eiichirou Tanaka, Ryosuke Niwa, Kazuki Osawa, Keyaki Nakajima, Keiichi Muramatsu, Keiichi Watanuki, Shozo Saegusa, Louis Yuge
Motion assistance apparatus enabled for neuro-rehabilitation of patients and for the promotion of exercise for the elderly. AIM (2015)