Fast Exact k-Means, k-Medians and Bregman Divergence Clustering in 1D

Grønlund2017Vector quantization and Voronoi theory

Exact 1-D grouping DP and parametric minimisation of the tilt dual (2 Sep 2026)

Added by the independent DS19 audit (AUDITS/AUDIT-DS-PRACTICAL-CERTIFIED-SOLVER-001.md).

  • Wang & Song (2011) implement the contiguous 1-D kk-means DP in O(kn2)O(kn^2) time and O(kn)O(kn) space — exactly the fixed-tilt evaluation DS19.2 describes.
  • Grønlund et al. (2017, arXiv:1701.07204; pp. 1–2 read) survey the exact 1-D problem: the DP recurrence runs in O(nlog⁡n+kn)O(n\log n+kn), or O(kn)O(kn) on sorted input, by monotone-matrix search, and the weighted discrete scalar quantization form is covered. Transfers: the fixed-tilt bound is O(KN)O(KN) after sorting. Does not transfer: exact ties of tilted values are not treated; the audit's tie lemma (report §7.2) shows the DP value is tie-order independent.
  • Megiddo (1983) parametric search and Toledo (1993; primary text read) fixed-dimension concave maximisation with polynomial comparisons. With F=−vKF=-v_K and the interval DP as a degree-2 evaluator, the exact tilt dual minimum is computable with polynomially many arithmetic operations for fixed dλd_\lambda and variable KK. Does not transfer: neither source bounds bit complexity; at dλ=1d_\lambda=1 the audit's root-separation bisection supplies a polynomial-bit algorithm (report §7.5), and OPEN-DS-TILT-DUAL-EXACT-COMPLEXITY retains the bit question for fixed dλ≥2d_\lambda\ge2 and the whole question for variable dλd_\lambda.
  • Carstensen (1983; secondary record) is the original nΩ(log⁡n)n^{\Omega(\log n)} parametric shortest-path breakpoint construction behind the Gajjar–Radhakrishnan warning: the envelope must not be materialised, which parametric search avoids. See LITERATURE/audits/AUDIT-DS-PRACTICAL-CERTIFIED-SOLVER-2-September-2026.md for the six-field table.

Gronlund, Larsen, Mathiasen, Nielsen, Schneider, Song; arXiv:1701.07204 v4 (2018). Primary text pp. 1-2 read 2 Sep 2026. The contiguous 1-D k-means DP runs in O(kn^2), and in O(n log n + kn) (O(kn) on sorted input) by monotone-matrix search; the weighted discrete scalar quantization form is covered. Improves DS19.2's fixed-tilt O(KN^2) evaluation bound to O(KN) after sorting.

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