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Imran, Megat Farez Azril Zuhairi, Syed Mubashir Ali, Zeeshan Shahid, Muhammad Mansoor Alam and Mazliham Mohd Su?ud
Anomaly detection (AD) has captured a significant amount of focus from the research field in recent years, with the rise of the Internet of Things (IoT) application. Anomalies, often known as outliers, are defined as the discovery of anomalous occurrence...
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Cindy Trinh, Silvia Lasala, Olivier Herbinet and Dimitrios Meimaroglou
This article investigates the applicability domain (AD) of machine learning (ML) models trained on high-dimensional data, for the prediction of the ideal gas enthalpy of formation and entropy of molecules via descriptors. The AD is crucial as it describe...
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Jiamu Li, Ji Zhang, Mohamed Jaward Bah, Jian Wang, Youwen Zhu, Gaoming Yang, Lingling Li and Kexin Zhang
When dealing with high-dimensional data, such as in biometric, e-commerce, or industrial applications, it is extremely hard to capture the abnormalities in full space due to the curse of dimensionality. Furthermore, it is becoming increasingly complicate...
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Terrance E. Boult, Nicolas M. Windesheim, Steven Zhou, Christopher Pereyda and Lawrence B. Holder
Algorithms for automated novelty detection and management are of growing interest but must address the inherent uncertainty from variations in non-novel environments while detecting the changes from the novelty. This paper expands on a recent unified fra...
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Jiyong Kim and Minseo Park
Lifelogs are generated in our daily lives and contain useful information for health monitoring. Nowadays, one can easily obtain various lifelogs from a wearable device such as a smartwatch. These lifelogs could include noise and outliers. In general, the...
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