Unbounded Characteristic and Universal Kernels

arXiv:2610.09731 · math.ST, cs.LG, stat.ML, stat.TH · Submitted 2026-10-07 · Read on arXiv

math.ST, cs.LG, stat.ML, stat.TH

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Hilbert Space — 16× in this paper · explained in 2 episodes
• Homogeneity — 8× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 2× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• In Algorithmic Learning Theory — 1× in this paper
• Trace — 1× in this paper · explained in 2 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD
• A Practical Introduction to Kernel Discrepancies: MMD, HSIC & KSD

Related papers

• Conformal Prediction for Dyadic Regression Under Complex Missingness
• Sharp Asymptotic Theory of Maximum Likelihood Estimation for Gaussian Processes with an RBF Kernel
• Bentkus-type asymptotic e-values
• High-Dimensional Asymptotics of Differentially Private PCA
• A proximal gradient algorithm for composite log-concave sampling
• KL Convergence Guarantees for Score diffusion models under minimal data assumptions