Truncated Kernel Stochastic Gradient Descent with General Losses and Spherical Radial Basis Functions

arXiv:2510.04237 · cs.LG · Submitted 2025-10-05 · Read on arXiv

cs.LG

Submitted: 2025-10-05

Updated: 2026-09-08

Comments: 71 pages, 30 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Loss Function — 26× in this paper · explained in 2 episodes
Regularization — 21× in this paper · explained in 3 episodes
Generalization — 13× in this paper · explained in 13 episodes
Robustness — 10× in this paper · explained in 5 episodes
Hilbert Space — 7× in this paper · explained in 2 episodes
Accuracy — 6× in this paper · explained in 1 episode
Consistency — 5× in this paper · explained in 3 episodes
Convergence Guarantees — 3× in this paper · explained in 3 episodes
Minimax Optimal Rates — 3× in this paper · explained in 2 episodes
Physical Constraints — 3× in this paper · explained in 7 episodes
Stochastic Gradient Descent (SGD) — 2× in this paper · explained in 5 episodes
Benchmark — 1× in this paper · explained in 2 episodes
Chebyshev Polynomials — 1× in this paper · explained in 2 episodes
Conservation Laws — 1× in this paper · explained in 3 episodes
Higher-order derivatives — 1× in this paper · explained in 2 episodes
Non-asymptotic Analysis — 1× in this paper · explained in 2 episodes
Objective Function — 1× in this paper · explained in 2 episodes
Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 3 episodes
Trace — 1× in this paper · explained in 2 episodes