Author

Akira Tamamori

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#machine learning Preprint Sep 2026

Information Geometric Self-Organization at the Edge of Stability in High-Capacity Kernel Associative Memories

High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit exceptional storage capabilities and robustness. Previous empirical studies identified a hyperparameter regime, the"Ridge of Optimization,"where attractor stability is maximized. However, the geometric nature of this regime and the opt...

Akira Tamamori · 1 citation

#machine learning Preprint Sep 2026

Geometry of learning dynamics: Gradient descent versus natural gradient on the ridge of optimization

High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit a"Ridge of Optimization"characterized by extreme stability and a highly skewed weight spectrum. However, the dynamical process by which learning converges to this critical regime has remained unclear. This paper provides a geometric an...

Akira Tamamori · 1 citation