Integral inequality for nearest-neighbor classification

From papers

Let XfXX\sim f_X and ZfZZ\sim f_Z be independent random variables, where fXf_X and fZf_Z are densities with cumulative distribution functions FXF_X and FZF_Z, respectively. Integral inequality conjecture. The inequality

r=α=0(FX(r)FZ(r))(fX(rα)fZ(r+α)fX(r+α)fZ(rα))dαdr0\int_{r=-\infty}^{\infty}\int_{\alpha=0}^{\infty}\left(F_X(r)-F_Z(r)\right)\left(f_X(r-\alpha)f_Z(r+\alpha)-f_X(r+\alpha)f_Z(r-\alpha)\right)\,d\alpha\,dr\geq 0

holds. This inequality is presented as a sufficient-and-necessary reformulation of the expected-error comparison underlying the proposed nearest-neighbor rule, and its validity is left unresolved.

Progress summary

Open

No public discussion or published progress on this conjecture was found.

No public discussion or published progress was found.

Current status (as of August 2026): The conjecture appears open, with no recorded public activity establishing either the inequality or a counterexample.

Sources & referencesView supporting material

Primary source

Kevin Bleakley, “Extreme change-point detection”, arXiv:2403.19237 (2024).

Solutions 1

Counterexample

The integral can be strictly negative for explicit absolutely continuous probability densities.

For cRc\in\mathbb R, define

uc(t)=51{tc<1/10},u_c(t)=5\mathbf1_{\{|t-c|<1/10\}},

and take

fX=14u2+34u5,fZ=18u0+18u3+34u5.f_X=\frac14u_2+\frac34u_5, \qquad f_Z=\frac18u_0+\frac18u_3+\frac34u_5.

Both are probability densities. Write D=FXFZD=F_X-F_Z, and denote the conjectured integral by II. The substitution

x=rα,z=r+α,drdα=12dxdzx=r-\alpha,\qquad z=r+\alpha, \qquad dr\,d\alpha=\frac12\,dx\,dz

gives

I=12x<zD(x+z2)(fX(x)fZ(z)fX(z)fZ(x))dxdz.I=\frac12\int_{x<z} D\left(\frac{x+z}{2}\right) \left(f_X(x)f_Z(z)-f_X(z)f_Z(x)\right)\,dx\,dz.

At the ordered centers (0,2,3,5)(0,2,3,5), the respective component-mass vectors are

p=(0,1/4,0,3/4),q=(1/8,0,1/8,3/4).p=(0,1/4,0,3/4), \qquad q=(1/8,0,1/8,3/4).

For distinct centers ci<cjc_i<c_j, all corresponding midpoints lie in the same gap between the four supports. Thus DD is constant on that entire block, and

I=12i<jD(ci+cj2)(piqjpjqi).I=\frac12\sum_{i<j} D\left(\frac{c_i+c_j}{2}\right) (p_iq_j-p_jq_i).

The complete exact calculation is

(ci,cj)D((ci+cj)/2)piqjpjqicontribution to I(0,2)1/81/321/512(0,3)1/800(0,5)1/83/323/512(2,3)1/81/321/512(2,5)03/160(3,5)03/320\begin{array}{c|c|c|c} (c_i,c_j)&D((c_i+c_j)/2)&p_iq_j-p_jq_i& \text{contribution to }I\\ \hline (0,2)&-1/8&-1/32&1/512\\ (0,3)&-1/8&0&0\\ (0,5)&1/8&-3/32&-3/512\\ (2,3)&1/8&1/32&1/512\\ (2,5)&0&3/16&0\\ (3,5)&0&-3/32&0 \end{array}

and hence

I=1512<0.\boxed{I=-\frac1{512}<0}.

The same construction works with smooth densities: replace every ucu_c by the translate of any normalized CC^\infty bump supported in (1/10,1/10)(-1/10,1/10). Every midpoint remains in the same gap, so the exact value 1/512-1/512 is unchanged.

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Shivam Patel ·