12 citations · 15 across the 3 of their papers we have counts for
3 papers
Unsupervised learning-based structural analysis: Search for a characteristic low-dimensional space by local structures in atomistic simulations
Ryo Tamura, Momo Matsuda, Jianbo Lin +3
Owing to the advances in computational techniques and the increase in computational power, atomistic simulations of materials can simulate large systems with higher accuracy. Compl…
Multiclass spectral feature scaling method for dimensionality reduction
Momo Matsuda, Keiichi Morikuni, Akira Imakura +2
Irregular features disrupt the desired classification. In this paper, we consider aggressively modifying scales of features in the original space according to the label information…
Spectral feature scaling method for supervised dimensionality reduction
Momo Matsuda, Keiichi Morikuni, Tetsuya Sakurai
Spectral dimensionality reduction methods enable linear separations of complex data with high-dimensional features in a reduced space. However, these methods do not always give the…