A density-weighted pinball loss derived via Taylor expansion, estimated with a three-headed quantile network, targets improved conditional coverage in conformal prediction with non-asymptotic guarantees.
Standard arguments for quantile regression imply that the expected pinball risk satisfies the local quadratic growth condition Rpin(q)− R pin(q⋆)≥ bw 2 ∥q−q ⋆∥2 L2(PX ),∀q∈ G r
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Colorful Pinball: Density-Weighted Quantile Regression for Conditional Guarantee of Conformal Prediction
A density-weighted pinball loss derived via Taylor expansion, estimated with a three-headed quantile network, targets improved conditional coverage in conformal prediction with non-asymptotic guarantees.