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Equation 5 · Part 2 · The Hardest Unsolved Problems in Small and On-Device AI

Symbol T

Δˉ=1T∑t=1T(AcctFP−AcctQ)\bar{\Delta} = \frac{1}{T}\sum_{t=1}^{T}\left(\mathrm{Acc}_t^{FP} - \mathrm{Acc}_t^{Q}\right)
TT

What this part means

T occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.

Its job in the formula

T occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.

The passage around this formula

Formally, if a model is evaluated on T tasks with full-precision accuracy AcctFP\mathrm{Acc}_t^{FP} and quantized accuracy AcctQ\mathrm{Acc}_t^{Q} on task t , a benchmark table typically reports the mean regression Δˉ=1T∑t=1T(AcctFP−AcctQ)\bar{\Delta} = \frac{1}{T}\sum_{t=1}^{T}\left(\mathrm{Acc}_t^{FP} - \mathrm{Acc}_t^{Q}\right). while what governs whether any individual deployment is safe to ship is closer to the worst-case regression

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Learn the underlying idea

A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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Sources cited in the article section

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