Author

Haruki Yokota

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Preprint Sep 2026

Multivariate signal restoration via Multifold Graph Learning

We propose a method for restoring noisy and incomplete multivariate signals by learning multifold graphs. Spatial relationships among channels can be utilized to recover missing values and suppress noise. However, these relationships can vary across frequency components and observation windows while retaining common co...

Haruki Yokota, Yuichi Tanaka · 0 citations

#machine learning Jun 2025

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming

Extensive experimental results on synthetic and real-world datasets show that the balanced graph learning method outperforms competing methods and enables reuse of spectral filters, wavelets, and graph neural nets constructed for positive graphs.

Haruki Yokota, Hiroshi Higashi, Yuichi Tanaka et al. · arXiv.org · 0 citations