Kazuki Osawa

Orcid: 0000-0001-6390-9797

According to our database1, Kazuki Osawa authored at least 17 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Improving Continual Learning by Accurate Gradient Reconstructions of the Past.
Trans. Mach. Learn. Res., 2023

ASDL: A Unified Interface for Gradient Preconditioning in PyTorch.
CoRR, 2023

PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices.
Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias.
Proceedings of the International Conference on Machine Learning, 2023

2022
Scalable and Practical Natural Gradient for Large-Scale Deep Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Efficient Quantized Sparse Matrix Operations on Tensor Cores.
Proceedings of the SC22: International Conference for High Performance Computing, 2022

Neural Graph Databases.
Proceedings of the Learning on Graphs Conference, 2022

2020
Development of the Image-based Flight and Tree Measurement System in a Forest using a Drone.
J. Robotics Netw. Artif. Life, 2020

Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rich Information is Affordable: A Systematic Performance Analysis of Second-order Optimization Using K-FAC.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019
Practical Deep Learning with Bayesian Principles.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Performance Optimizations and Analysis of Distributed Deep Learning with Approximated Second-Order Optimization Method.
Proceedings of the 48th International Conference on Parallel Processing, 2019

Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Second-order Optimization Method for Large Mini-batch: Training ResNet-50 on ImageNet in 35 Epochs.
CoRR, 2018

2017
Accelerating Matrix Multiplication in Deep Learning by Using Low-Rank Approximation.
Proceedings of the 2017 International Conference on High Performance Computing & Simulation, 2017

Evaluating the Compression Efficiency of the Filters in Convolutional Neural Networks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

2015
Motion assistance apparatus enabled for neuro-rehabilitation of patients and for the promotion of exercise for the elderly.
Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2015


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