An information processing device which performs semi-supervised learning is provided with: a dictionary input circuit for acquiring a dictionary, a parameter group used by an identification device; a boundary determination circuit which obtains an identification boundary for the dictionary on the basis of the dictionary, supervised data, and labelled unsupervised data; a labelling circuit which labels the unsupervised data in accordance with the identification boundary; a loss calculation circuit which calculates the sum total of supervised-data loss calculated in accordance with the labels assigned in advance and the labels based on the identification boundary, and unsupervised-data loss calculated such that further from the identification boundary the smaller the loss; a dictionary update circuit which updates the dictionary such that the sum-total loss is reduced; and a dictionary output circuit which outputs the updated dictionary.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing device which uses supervised data and unsupervised data to perform semi-supervised learning, the information processing device comprising: a dictionary input circuit configured to obtain a dictionary that includes a parameter group used in an identification device; a boundary determination circuit configured to search for an identification boundary of the dictionary on the basis of the dictionary, the supervised data, and labeled unsupervised data; a label assignment circuit configured to assign a label to the unsupervised data in accordance with the identification boundary; a loss calculation circuit configured to calculate a sum of a loss of the supervised data which is calculated in accordance with a label based on the identification boundary and a preassigned label and a loss of the unsupervised data which is calculated in such a manner as to be smaller as more distant from the identification boundary; a dictionary update circuit configured to update the dictionary in such a manner as to decrease the sum of the losses; and a dictionary output circuit configured to output the updated dictionary. 2. The information processing device according to claim 1, wherein the loss calculation circuit uses a function representing Gaussian distribution when calculating the loss of the unsupervised data. 3. The information processing device according to claim 1, wherein the dictionary update circuit updates the dictionary by using a differential value of the sum of the losses. 4. The information processing device according to claim 1, wherein the dictionary output circuit determines, on the basis of a change amount of the sum of the losses in response to an update of the dictionary, either output of the dictionary or continuation of update of the dictionary. 5. The information processing device according to claim 1, further comprising: an identification circuit configured to identify by using the dictionary, data subject to identification which is input. 6. An information processing method executed by an information processing device which uses supervised data and unsupervised data to perform semi-supervised learning, the information processing method comprising: obtaining a dictionary which includes a parameter group used in an identification device; determining an identification boundary of the dictionary on the basis of the dictionary, the supervised data, and labeled unsupervised data; assigning a label to the unsupervised data in accordance with the identification boundary; calculating a sum of a loss of the supervised data which is calculated in accordance with the label based on the identification boundary and a preassigned label and a loss of the unsupervised data which is calculated in such a manner as to be smaller as more distant from the identification boundary; updating the dictionary in such a manner as to decrease the sum of the losses; and outputting the updated dictionary. 7. A non-transitory computer readable medium storing a program executed by an information processing device which uses supervised data and unsupervised data to perform semi-supervised learning, the program causing the information processing device to execute: obtaining a dictionary which includes a parameter group used in an identification device; searching for an identification boundary of the dictionary on the basis of the dictionary, the supervised data, and labeled unsupervised data; assigning a label to the unsupervised data in accordance with the identification boundary; calculating a sum of a loss of the supervised data which is calculated in accordance with the label based on the identification boundary and a preassigned label and a loss of the unsupervised data which is calculated in such a manner as to be smaller as more distant from the identification boundary; updating the dictionary in such a manner as to decrease the sum of the losses; and outputting the updated dictionary. 8. The information processing method according to claim 6, wherein the information processing device uses a function representing Gaussian distribution when calculating the loss of the unsupervised data. 9. The information processing method according to claim 6, wherein the dictionary update circuit updates the dictionary by using a differential value of the sum of the losses. 10. The information processing method according to claim 6, wherein the dictionary output circuit determines, on the basis of a change amount of the sum of the losses in response to an update of the dictionary, either output of the dictionary or continuation of update of the dictionary. 11. The information processing method according to claim 6, further including: identifying, by using the dictionary, data subject to identification which is input. 12. The program according to claim 7, causing the information processing device to perform the loss calculation function in which a function representing Gaussian distribution is used when calculating the loss of the unsupervised data. 13. The program according to claim 7, causing the information processing device to perform the dictionary update function of updating the dictionary by using a differential value of the sum of the losses. 14. The program according to claim 7, causing the information processing device to perform the dictionary update function of determining, on the basis of a change amount of the sum of the losses in response to an update of the dictionary, either output of the dictionary or continuation of update of the dictionary. 15. The program according to claim 7, causing the information processing device to further perform an identification function of identifying by using the dictionary, data subject to identification which is input.