Abstract: A learning model optimization device includes a binarization matrix setting unit configured to set a binarization matrix m in which each element is a numerical value of “0” or “1” and a transformed matrix setting unit configured to set a transformed matrix M having, as an element, a product of each element of the parameter matrix and each element of the binarization matrix in the same row and the same column. The learning model optimization device further includes a learning unit configured to perform machine learning using the transformed matrix M and change a numerical value of each element of the binarization matrix m such that a result of the machine learning approaches teacher data, thereby optimizing the binarization matrix m, and a re-randomization processing unit configured to change again a parameter of the parameter matrix w.

Abstract: A processing server includes a storage device that stores program revision data for identifying a revision of a program and the program of the revision, and runtime revision data for identifying a revision of runtime data input and output to and from the program and the runtime data of the revision, a generating unit that, after receiving a revision of a program that is a target of execution, secures an execution area in the storage device and generates execution target data for executing the program of the revision that is the target of execution in the secured execution area, and an executing unit that executes the execution target data using the runtime data that is the target of execution in the execution area.