Extracting sequences from d-dimensional input data for sequential processing with neural networks

Abstract

A method and computer program product for obtaining values are run using a neural network according to a machine learning algorithm. One embodiment may comprise accessing one or more datafiles of input data, where the input data is representable in a d-dimensional space, with d>1. The method may explore N distinct paths of the input data in the d-dimensional space, where N≥1, and collects data along the N distinct paths explored to respectively form N sequences of M objects each, with M≥2. For one or more sequences of the N sequences formed, values obtained from the M objects of each sequence may be coupled into one or more input nodes of a neural network, which is then run according to the machine learning algorithm to obtain L output values from, L≥1.