Approximate leave-one-out conformal prediction achieves asymptotic coverage and efficiency comparable to exact leave-one-out methods with substantially lower computational cost.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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ParamBoost improves GAMs by fitting piecewise cubic polynomials via gradient boosting and supports constraints for continuity, monotonicity, convexity, and feature interactions.
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Accelerating Conformal Prediction via Approximate Leave-One-Out
Approximate leave-one-out conformal prediction achieves asymptotic coverage and efficiency comparable to exact leave-one-out methods with substantially lower computational cost.
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ParamBoost: Gradient Boosted Piecewise Cubic Polynomials
ParamBoost improves GAMs by fitting piecewise cubic polynomials via gradient boosting and supports constraints for continuity, monotonicity, convexity, and feature interactions.