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Equation 9 · Part 2 · Embeddings and the Geometry of Similarity

Symbol E

lim⁡d→∞E ⁣[Dmax⁡k−Dmin⁡kd1/k−1/2]=C⋅1(k+1)1/k12k+1,\lim_{d \to \infty} \mathbb{E}\!\left[ \frac{D_{\max}^{k} - D_{\min}^{k}}{d^{1/k - 1/2}} \right] = C \cdot \frac{1}{(k+1)^{1/k}} \sqrt{\frac{1}{2k+1}},
E\mathbb{E}

What this part means

The expected value operator: the probability-weighted average of the quantity inside its brackets.

Its job in the formula

E is part of the quantity the equation computes from the expression on the right.

The passage around this formula

Aggarwal, Hinneburg and Keim then showed the rate depends on the norm. For uniform data under an LkL_k metric, the expected gap between the farthest and nearest distances scales as lim⁡d→∞E ⁣[Dmax⁡k−Dmin⁡kd1/k−1/2]=C⋅1(k+1)1/k12k+1\lim_{d \to \infty} \mathbb{E}\!\left[ \frac{D_{\max}^{k} - D_{\min}^{k}}{d^{1/k - 1/2}} \right] = C \cdot \frac{1}{(k+1)^{1/k}} \sqrt{\frac{1}{2k+1}}. with C constant, while typical distances themselves grow like d1/kd^{1/k} . Relative contrast therefore decays with dimension, and the constant shrinks as k rises — which is why they conclude that L1L_1 is preferable to L2L_2 in high dimensions, L2L_2 to L3L_3 , and that fractional norms preserve contrast better still [ 12 ] .

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Probability assigns a number from 0 to 1 to an event under a stated model. Zero means impossible within that model; one means certain.

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Sources cited in the surrounding passage

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