Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function
Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function explores This paper presents a new method for improving uncertainty bounds in multivariate kernel regression using Gaussian processes.. Commercial viability score: 2/10 in Kernel Regression.
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