SplineSketch: Even More Accurate Quantiles with Error Guarantees
Summary: Introduces SplineSketch, a streaming quantile sketch for numeric data that maintains a dynamic subdivision of the value range and fits a monotone cubic spline to the empirical distribution for much tighter interpolation. Achieves near‑optimal uniformly bounded rank-error guarantees while empirically beating t‑digest by 2–20×. (summarized by gpt-5-mini on Feb 11 2026)
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