rkhs

This paper introduces logical embeddings for argument analysis, providing a mathematical framework that outperforms standard embedding methods by focusing on logical semantics and argumentation structures.

This paper proves that for large bandwidths, the Gaussian RBF reproducing kernel Hilbert space becomes asymptotically isometric to Euclidean space, causing kernel PCA to converge to linear PCA. A measure of data eccentricity predicts convergence behavior in top principal directions.