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On the Performance of the Depth First Search Algorithm in Supercritical Random Graphs
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abstract
We consider the performance of the Depth First Search (DFS) algorithm on the random graph $G\left(n,\frac{1+\epsilon}{n}\right)$, $\epsilon>0$ a small constant. Recently, Enriquez, Faraud and M\'enard [2] proved that the stack $U$ of the DFS follows a specific scaling limit, reaching the maximal height of $(1+o_{\epsilon}(1))\epsilon^2n$. Here we provide a simple analysis for the typical length of a maximum path discovered by the DFS.
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Cited by 1 Pith paper
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DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding
DeepTraverse is a weight-tied residual network plus squeeze-and-excitation attention, framed as depth-first search, with claimed efficiency gains that rest on a questionable ImageNet subset comparison.
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