Noise Contrastive Estimation of Coupled Energy-Based Model for Anomaly Detection 


Vol. 50,  No. 10, pp. 1497-1504, Oct.  2025
10.7840/kics.2025.50.10.1497


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  Abstract

In this paper, a new coupled energy-based model (CEBM) for anomaly detection and noise contrast estimation (NCE) technique for learning it are presented. The structure of CEBM consists of the product of two unnormalized probability distributions, each of which is defined by an energy function with a deep neural network. We derive the objective function of NCE by using one distribution of CEBM as a noise distribution and present a parameter update method using the gradient descent method. An experiment using ECG, UNSW and MNIST/Fashion-MNIST is conducted to evaluate the anomaly detection performance of the proposed technique. As a result of the experiment, the CEBM learned with the proposed NCE shows higher F1-score than the existing EBMs in all data sets.

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[IEEE Style]

D. K. Kim, "Noise Contrastive Estimation of Coupled Energy-Based Model for Anomaly Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 10, pp. 1497-1504, 2025. DOI: 10.7840/kics.2025.50.10.1497.

[ACM Style]

Dong Kook Kim. 2025. Noise Contrastive Estimation of Coupled Energy-Based Model for Anomaly Detection. The Journal of Korean Institute of Communications and Information Sciences, 50, 10, (2025), 1497-1504. DOI: 10.7840/kics.2025.50.10.1497.

[KICS Style]

Dong Kook Kim, "Noise Contrastive Estimation of Coupled Energy-Based Model for Anomaly Detection," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 10, pp. 1497-1504, 10. 2025. (https://doi.org/10.7840/kics.2025.50.10.1497)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880