Author

Hiroshi Higashi

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#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

Conference Open access Jul 2026

WREN: Low Light Image Enhancement Using Retinex theory-based Double U-Net-like Structures

WREN is an LLIE neural network with double U-Net-like structures trained end-to-end with a scale-invariant loss function, which gives robustness against the illumination scaling, and achieves the state-of-the-art performance across multiple datasets.

Reina Kaneko, Junya Hara, Hiroshi Higashi et al. · International Conference on... · 0 citations