Abstract: An information processing device that displays, on a screen, cards associated with a series of respective processes performed on data and that defines a flow of the series of processes by connecting the cards by first lines, the information processing device includes processing circuitry configured to receive an operation performed by a user, perform, when an operation for connecting the cards by second lines that represent synchronization of parameters is received, a setting for allowing the parameters of the respective processes associated with the plurality of cards connected by the second lines to be synchronized, and make, when a parameter of one of the cards is changed out of the plurality of cards in which the setting for allowing the parameters to be synchronized has been performed, a same change on the parameters of the respective processes associated with the plurality of cards connected by the second lines.

Abstract: An information processing device includes processing circuitry configured to perform data processing on data that is input from a card corresponding to a connection source display a graph that includes a plurality of cards each of which outputs a result of the associated data processing to a card corresponding to a connection destination and notify, when an input of a comment with respect to an area relevant to the graph that is displayed has been received, a terminal device used by a user relevant to the graph of information on the input comment.

Abstract: An information processing device that displays, on a screen, cards associated with a series of respective processes performed on data and that defines a flow of the series of processes by connecting the cards by first lines, the information processing device includes processing circuitry configured to receive an operation performed by a user, perform, when an operation for connecting the cards by second lines that represent synchronization of parameters is received, a setting for allowing the parameters of the respective processes associated with the plurality of cards connected by the second lines to be synchronized, and make, when a parameter of one of the cards is changed out of the plurality of cards in which the setting for allowing the parameters to be synchronized has been performed, a same change on the parameters of the respective processes associated with the plurality of cards connected by the second lines.

Abstract: A learning device includes processing circuitry configured to acquire a plurality of pieces of data, input the plurality of pieces of data acquired by the acquisition unit to a model as input data, and when obtaining output data output from the model, calculate a loss of the model based on the output data and a correct answer data, repeat update processing of updating weight of the model in accordance with a loss each time the first calculation unit calculates the loss, calculate a value contributing to interpretability of the model, and end the update processing when the loss calculated by the first calculation unit and the value calculated by the second calculation unit satisfy a predetermined condition.

Abstract: A learning device includes processing circuitry configured to acquire time series data related to a processing target, perform learning processing of updating parameters of a first model by using the time series data acquired as a data set for learning, and causing the first model to solve a first task, the first model including a neural network constituted of a plurality of layers, and perform learning processing of updating parameters of a second model by using the data set for learning, and causing the second model to solve a second task different from the first task, the second model including a neural network using, as initial values, the parameters of the first model subjected to the learning processing performed.

Abstract: An information processing device includes processing circuitry configured to acquire a plurality of pieces of data, input the pieces of data to a model as input data, and in a case of obtaining output data output from the model, calculate an importance of each component of the input data with respect to the output data based on the input data and the output data, acquire a binding coefficient indicating a relevance among components of the input data, calculate a bound importance obtained by applying the binding coefficient to the importance, and create information indicating the bound importance of each input item.

Abstract: An information processing device includes processing circuitry configured to obtain a plurality of sets of data related to a processing target, group relationships among the sets of data that are obtained, based on group information set in advance, calculate degrees of importance indicating strengths of cause-and-effect relationships among sets of data included in each group, and calculate, based on the degrees of importance, estimation values indicating the cause-and-effect relationships among sets of data.

Abstract: Provided are a data processing apparatus, a data processing method and a computer program. The data processing apparatus processes measured data of a plurality of power storage devices, comprises: a storage unit that stores determination model using an autoencoder, which is trained to reproduce measured data when measured data is input, the input measured data being of each of the plurality of energy storage devices or of each group of energy storage devices, which is grouped from the plurality of the energy storage devices; and a processor. The processor determines the measured data of an odd energy storage device out of the measured data for each of the energy storage devices or for each group of energy storage devices based on an error between reproduced measured data, which is output when the measured data is input to the determination model, and the measured data.

Abstract: A learning device includes processing circuitry configured to collect a plurality of data, calculate, when inputting the plurality of data as input data to a model and obtaining output data that is output from the model, an attribution that is a degree of contribution of each element of the input data to the output data, based on the input data and the output data, and apply a restriction on the attribution thereto and learn the model.