Nec Corporation

Taiki Miyagawa

Akinori Ebihara

An information processing apparatus includes: an acquisition unit that obtains a plurality of elements included in series data; a calculation unit that calculates a likelihood ratio indicating a likelihood that the series data are derived from the same target as that of predetermined data, on the basis of at least two consecutive elements of the plurality of elements; and a determination unit that determines whether or not the series data are derived from the same target as that of the predetermined data, on the basis of the likelihood ratio. The calculation unit calculates the likelihood ratio in view of a degree of similarity or difference between the series data and the predetermined data. According to the information processing apparatus, it is possible to accurately determine whether or not the series data is derived from the same target as that of the predetermined data.

Information processing apparatus, information processing method, and computer program

In order to suitably perform labeling even in a case where there is an unclear event boundary, a classification apparatus () includes: an acquiring means () for acquiring series data; and a class label assigning means () for assigning a class label to each piece of element data contained in the series data, by repeatedly applying quickest change detection to the series data.

Classification apparatus, classification method, and recording medium

A learning device includes a class classification learning unit that learns class classification of a classification target by using a loss function in which a loss is calculated to become smaller as a magnitude of a difference between a function value obtained by inputting a log-likelihood ratio to a function having a finite value range and a constant associated with a correct answer to the class classification of the classification target becomes smaller, the log-likelihood ratio being the logarithm of a ratio between the likelihood that the classification target belongs to a first class and the likelihood that the classification target belongs to a second class.

Learning device, learning method, and recording medium

An information processing system () includes: an acquisition unit () configured to sequentially acquire a plurality of elements included in sequential data; a first calculation unit () configured to calculate, for each of the plurality of elements, a first indicator indicating which one of a plurality of classes the element belongs to; a weight calculation unit () configured to calculate, for each of the plurality of elements, a weight according to a confidence related to calculation of the first indicator; a second calculation unit () configured to calculate, based on the first indicators each weighted with the weight, a second indicator indicating which one of the plurality of classes the sequential data belongs to; and a classification unit () configured to classify the sequential data as any one of the plurality of classes, based on the second indicator. According to such an information processing system, sequential data can be appropriately classified.

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Tokyo, Japan

Taiki Miyagawa