Year: 2024
Type: preprint
Abstract: We present a series of algorithms in tensor networks for anomaly detection in datasets, by using data compression in a Tensor Train representation. These algorithms consist of preserving the structure of normal data in compression and deleting the structure of anomalous data. The algorithms can be applied to any tensor network representation. We test the effectiveness of the methods with digits and Olivetti faces datasets and a cybersecurity dataset to determine cyber-attacks.
Source: arXiv (Cornell University)
Authors: Ali, Alejandro Mata, de Leceta, Aitor Moreno Fdez., Rubio, Jorge López
Institution: Euskadiko Parke Teknologikoa
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403780451