Variance-based Gradient Compression for Efficient Distributed Deep Learning. - Yusuke Tsuzuku; Hiroto Imachi; Takuya Akiba (ICLR (Workshop), 2018)

Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks. - Yusuke Tsuzuku; Issei Sato; Masashi Sugiyama (NeurIPS, 2018)

On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions. - Yusuke Tsuzuku; Issei Sato (CVPR, 2019)

Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis. - Yusuke Tsuzuku; Issei Sato; Masashi Sugiyama (ICML, 2020)