A new planted ranked subgraph model in directed graphs is analyzed, with exact statistical and computational thresholds for detection and recovery in the log-density and extreme regimes.
Sorting with Recurrent Comparison Errors
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We present a sorting algorithm for the case of recurrent random comparison errors. The algorithm essentially achieves simultaneously good properties of previous algorithms for sorting $n$ distinct elements in this model. In particular, it runs in $O(n^2)$ time, the maximum dislocation of the elements in the output is $O(\log n)$, while the total dislocation is $O(n)$. These guarantees are the best possible since we prove that even randomized algorithms cannot achieve $o(\log n)$ maximum dislocation with high probability, or $o(n)$ total dislocation in expectation, regardless of their running time.
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Statistical inference of a ranked community in a directed graph
A new planted ranked subgraph model in directed graphs is analyzed, with exact statistical and computational thresholds for detection and recovery in the log-density and extreme regimes.