Efficient computation of normalized maximum likelihood coding for Gaussian mixtures with its applications to optimal clustering. - So Hirai; Kenji Yamanishi (ISIT, 2011)

Detecting changes of clustering structures using normalized maximum likelihood coding. - So Hirai; Kenji Yamanishi (KDD, 2012)

Normalized Maximum Likelihood Coding for Exponential Family with Its Applications to Optimal Clustering - So Hirai; Kenji Yamanishi (CoRR, 2012)

Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering. - So Hirai; Kenji Yamanishi (IEEE Trans. Inf. Theory, 2013)

An Upper Bound on Normalized Maximum Likelihood Codes for Gaussian Mixture Models. - So Hirai; Kenji Yamanishi (CoRR, 2017)

Detecting Latent Structure Uncertainty with Structural Entropy. - So Hirai; Kenji Yamanishi (IEEE BigData, 2018)

Spectral-Pruning: Compressing deep neural network via spectral analysis. - Taiji Suzuki; Hiroshi Abe; Tomoya Murata; Shingo Horiuchi; Kotaro Ito; Tokuma Wachi; So Hirai; Masatoshi Yukishima; Tomoaki Nishimura (CoRR, 2018)

Detecting Model Changes and their Early Warning Signals Using MDL Change Statistics. - So Hirai; Kenji Yamanishi (IEEE BigData, 2019)

Correction to Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering. - So Hirai; Kenji Yamanishi (IEEE Trans. Inf. Theory, 2019)

Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error. - Taiji Suzuki; Hiroshi Abe; Tomoya Murata; Shingo Horiuchi; Kotaro Ito; Tokuma Wachi; So Hirai; Masatoshi Yukishima; Tomoaki Nishimura (IJCAI, 2020)

Detecting Gradual Structure Changes of Non-parametric Distributions via Kernel Complexity. - So Hirai; Kenji Yamanishi (IEEE BigData, 2021)

Detecting signs of model change with continuous model selection based on descriptive dimensionality. - Kenji Yamanishi; So Hirai (Appl. Intell., 2023)