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g(a)g(a)

Why this formula appears here

where A\mathcal{A} is a search space of candidate architectures designed in advance by the researchers, g(a) some measured deployment cost of architecture a , and B a budget the target device imposes. Every term in that equation is a documented design choice, and the choice of g turns out to be where the edge-specific literature does its most important work.

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gg

Symbol g

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aa

Symbol a

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Published contexts (2)

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g(a)g(a)

Equation 21 · Edge AI & Electronics

Shrink It, Train It Small, or Search for It: The Main Strategies for Small Models, Compared

This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text.

where A\mathcal{A} is a search space of candidate architectures designed in advance by the researchers, g(a) some measured deployment cost of architecture a , and B a budget the target device imposes. Every term in that equation is a documented design choice, and the choice of g turns out to be where the edge-specific literature does its most important work.

Equation guide → · Article →
g(a)g(a)

Equation 25 · Edge AI & Electronics

Shrink It, Train It Small, or Search for It: The Main Strategies for Small Models, Compared

This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text.

The first response changes what g(a) measures. Tan and colleagues built MnasNet’s rationale explicitly around the observation that operation counts are a poor stand-in for real efficiency, so the search “directly measures real-world inference latency by executing the model on mobile phones,” and reported an architecture 1.8x faster than MobileNetV2 at 0.5% higher accuracy, and 2.3x faster than NASNet at 1.2% higher accuracy [ 8 ] . That is a harder objective to satisfy than a proxy count, because it cannot be gamed by an architecture that is cheap on paper and slow in practice. The second response changes how often the expensive part of the search has to be paid at all. Cai and colleagues…

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