What is recorded here?
Fits lower and upper conditional quantiles on proper training data, then uses held-out signed interval errors to conformalize variable-width regression intervals.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Finite-sample guarantee is marginal under exchangeability, not exact coverage at each covariate or arbitrary distribution drift. Quantile regression and conformal prediction are inherited; interval efficiency depends on the fitted quantiles and sample split.
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People and systems
Yaniv Romano; Evan Patterson; Emmanuel J. Candès
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Conformalized Quantile Regression for adaptive prediction intervals
Fits lower and upper conditional quantiles on proper training data, then uses held-out signed interval errors to conformalize variable-width regression intervals.
Scientific scope
Finite-sample guarantee is marginal under exchangeability, not exact coverage at each covariate or arbitrary distribution drift. Quantile regression and conformal prediction are inherited; interval efficiency depends on the fitted quantiles and sample split.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Yaniv Romano; Evan Patterson; Emmanuel J. Candès
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.