Manifold-Regularized Minimax Probability Machine. - Kazuki Yoshiyama; Akito Sakurai (PSL, 2011)

Laplacian minimax probability machine. - Kazuki Yoshiyama; Akito Sakurai (Pattern Recognit. Lett., 2014)

Iteratively Training Look-Up Tables for Network Quantization. - Fabien Cardinaux; Stefan Uhlich; Kazuki Yoshiyama; Javier Alonso García; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (CoRR, 2018)

Differentiable Quantization of Deep Neural Networks. - Stefan Uhlich; Lukas Mauch; Kazuki Yoshiyama; Fabien Cardinaux; Javier Alonso García; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (CoRR, 2019)

Mixed Precision DNNs: All you need is a good parametrization. - Stefan Uhlich; Lukas Mauch; Fabien Cardinaux; Kazuki Yoshiyama; Javier Alonso García; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (ICLR, 2020)

Efficient Sampling for Predictor-Based Neural Architecture Search. - Lukas Mauch; Stephen Tiedemann; Javier Alonso García; Bac Nguyen Cong; Kazuki Yoshiyama; Fabien Cardinaux; Thomas Kemp (CoRR, 2020)

Iteratively Training Look-Up Tables for Network Quantization. - Fabien Cardinaux; Stefan Uhlich; Kazuki Yoshiyama; Javier Alonso García; Lukas Mauch; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (IEEE J. Sel. Top. Signal Process., 2020)

Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives. - Akio Hayakawa; Masato Ishii; Yoshiyuki Kobayashi; Akira Nakamura; Takuya Narihira; Yukio Obuchi; Andrew Shin; Takuya Yashima; Kazuki Yoshiyama (CoRR, 2021)

NDJIR: Neural Direct and Joint Inverse Rendering for Geometry, Lights, and Materials of Real Object. - Kazuki Yoshiyama; Takuya Narihira (CoRR, 2023)