Search
Now showing items 1-4 of 4
Adaptive Real-Time Method for Anomaly Detection Using Machine Learning
(MDPI AG, 2020-08-20)
[Abstract]
Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring ...
Fast deep autoencoder for federated learning
(Elsevier Ltd, 2023-11)
[Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...
Large scale anomaly detection in mixed numerical and categorical input spaces
(Elsevier, 2019)
[Abstract]: This work presents the ADMNC method, designed to tackle anomaly detection for large-scale problems with a mixture of categorical and numerical input variables. A flexible parametric probability measure is ...
Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?
(2024-07)
In the current landscape, user opinions exert an unprecedented influence on the trajectory of companies. In the field of online review platforms, these opinions, transmitted through text reviews and numerical ratings, ...