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Topic: #connections

Machine Learning Sorting

2018-05-15⊺11:52:14-05:00

“An O(N) Sorting Algorithm: Machine Learning Sorting”
Hanqing Zhao and Yueban Luo, arXiv, May 11, 2018
https://arxiv.org/pdf/1805.04272.pdf

The authors propose a new method for sorting a gigantic array of arbitrary values in linear time: Select a fixed number (say 1000) values from the array and sort them. Using these values as a training set, train a three-layer neural network to estimate the position in the sorted array that any given value will occupy. Set up an array of buckets equal in size to the original array. Feed each value in the array into the neural network and put it in the bucket corresponding to the network's prediction of the value's position in the sorted array. A linear-time amount of post-processing can now ensure that every value is in a bucket that is within a fixed distance of its position in the sorted array. Apply insertion sort on the almost-sorted values in the array of buckets to build the actual sorted array. Since insertion sort runs in linear time on almost-sorted arrays, the whole process, including the training of the neural network, takes linear time.

I wouldn't have thought of that one.

Next month in arXiv: Adversarial sorting examples.

#algorithms #machine-learning #connections

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John David Stone (havgl@unity.homelinux.net)

created June 1, 2014 · last revised December 10, 2018