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Found 2 papers, 2 papers with code
Regression Trees for Fast and Adaptive Prediction Intervals
Our approach is based on pursuing the coarsest partition of the feature space that approximates conditional coverage.
RFFNet: Large-Scale Interpretable Kernel Methods via Random Fourier Features
Kernel methods provide a flexible and theoretically grounded approach to nonlinear and nonparametric learning.
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