Distributed Kernel-based Learning with High-Probability Guarantees for Multi-Agent Applications
A distributed learning algorithm that enables a network of agents to collaboratively model an unknown nonlinear phenomenon with high-probability error bounds, without requiring strong a priori assumptions about the underlying function.
