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Equation 5 · Part 1 · The Hardest Unsolved Problems in Small and On-Device AI

Symbol barΔ

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)
Δˉ\bar{\Delta}

What this part means

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

Its job in the formula

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

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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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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