An information processing device includes, a memory, and a processor coupled to the memory and the processor configured to, acquire a neural network, divide the neural network into divided neural networks, identify, based on input-output characteristics of the divided neural networks, parameters of each of polynomial neural networks corresponding to each of the divided neural networks, and output another neural network generated by linking the identified polynomial neural networks.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing device comprising: a memory; and a processor coupled to the memory and the processor configured to: acquire a neural network, divide the neural network into divided neural networks, identify, based on input-output characteristics of the divided neural networks, parameters of each of polynomial neural networks corresponding to each of the divided neural networks, and output another neural network generated by linking the identified polynomial neural networks. 2. The information processing device according to claim 1, wherein a process of identifying the parameters includes arithmetic operations of a multivariable polynomial performed, in parallel arithmetic, by addition circuits and multiplication circuits. 3. The information processing device according to claim 1, wherein the processor changes the parameters in a case where correspondence values corresponding to the respective polynomial neural networks do not satisfy a predetermined condition. 4. The information processing device according to claim 1, wherein the parameters include a degree and a number of intermediate elements of each of the polynomial neural networks, intermediate elements including addition circuits and multiplication circuits, and the degree and the number of intermediate elements of each of the polynomial neural networks are identified without exceeding an upper limit number of the number of intermediate elements. 5. The information processing device according to claim 4, wherein based on the input-output characteristics of the divided neural networks, loss functions of the respective polynomial neural networks are calculated, it is determined whether or not each of the calculated loss functions are greater than a threshold value, and in a case where one of the calculated loss functions is greater than the threshold value, a corresponding one of the degrees and a corresponding one of the numbers of intermediate elements are changed. 6. The information processing device according to claim 5, wherein the parameters include weighting parameters, and the weighting parameters are calculated based on gradients calculated from the loss functions. 7. The information processing device according to claim 5, wherein, in a case where one of the loss functions after changing a corresponding one of the degrees and a corresponding one of the numbers of intermediate elements is greater than the threshold value, a corresponding one of the divided polynomial neural networks is further divided. 8. The information processing device according to claim 5, wherein the linking is a process for linking the polynomial neural networks identified based on the parameters for which the loss functions are less than or equal to the threshold value. 9. An information processing method executed by a computer, the method comprising: acquiring a neural network; dividing the neural network into divided neural networks; identifying, based on input-output characteristics of the divided neural networks, parameters of each of polynomial neural networks corresponding to each of the divided neural networks; and outputting another neural network generated by linking the identified polynomial neural networks. 10. A non-transitory computer-readable medium storing a program that causes a computer to execute a process comprising: acquiring a neural network; dividing the neural network into divided neural networks; identifying, based on input-output characteristics of the divided neural networks, parameters of each of polynomial neural networks corresponding to each of the divided neural networks; and outputting another neural network generated by linking the identified polynomial neural networks.