Parallel distributed kernel estimation

Non-parametric kernel methods are becoming more commonplace for data analysis, modeling, and inference. Unfortunately, these methods are known to be computationally burdensome. The burden increases as the amount of available data rises and can quickly overwhelm the computational resources present in modern desktop workstations. Approximation-based approaches exist which can dramatically reduce execution time, however, these approaches remain …