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Local Model Feature Transformations
[article]
2020
arXiv
pre-print
Local learning methods are a popular class of machine learning algorithms. The basic idea for the entire cadre is to choose some non-local model family, to train many of them on small sections of neighboring data, and then to 'stitch' the resulting models together in some way. Due to the limits of constraining a training dataset to a small neighborhood, research on locally-learned models has largely been restricted to simple model families. Also, since simple model families have no complex
arXiv:2004.06149v1
fatcat:mgosv4hjabbj7esu7ezdnr3sl4