Distributed machine learning device, distributed machine learning method, and distributed machine learning recording medium

Abstract

Provided is a distributed machine learning device which can efficiently converge a plurality of parameters. The distributed machine learning device includes: block configuration determination unit that determines a plurality of configurations of blocks each being a subset of a plurality of parameters used for a prediction model, and acquires a change amount of each subset of parameters belonging to the block, based on a result of executing processing of optimizing the plurality of parameters, and changes an element of the subset of the parameters in the block, based on the acquired change amount.