Yusuke Tsuzuku

Publication Activity (10 Years)

Years Active: 2018-2020
Publications (10 Years): 8

Top Topics

Scale Invariance

Bayesian Analysis

Top Venues

ICLR (Workshop)

Publications

Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis. ICML (2020)
Yusuke Tsuzuku, Issei Sato
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. CVPR (2019)
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis. CoRR (2019)
Yusuke Tsuzuku, Issei Sato
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. CoRR (2018)
Yusuke Tsuzuku, Hiroto Imachi, Takuya Akiba
Variance-based Gradient Compression for Efficient Distributed Deep Learning. CoRR (2018)
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks. NeurIPS (2018)
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks. CoRR (2018)
Yusuke Tsuzuku, Hiroto Imachi, Takuya Akiba
Variance-based Gradient Compression for Efficient Distributed Deep Learning. ICLR (Workshop) (2018)