Results 61 to 70 of about 247,960 (211)
VAE‐Based SPC for Botnet Detection in IoT Systems
Quality and Reliability Engineering International, EarlyView.ABSTRACT The rapid proliferation of Internet of Things (IoT) devices has created new security risks, particularly botnet infections. This paper proposes an unsupervised monitoring framework that combines a β$\beta$‐variational autoencoder (VAE) with multivariate statistical process control (SPC) for botnet detection in IoT networks.
Jorge Proaño +3 more
wiley +1 more source
Responsive Materials, EarlyView.Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen +8 more
wiley +1 more source
Enhanced Autoencoder-Based Fraud Detection: A Novel Approach With Noise Factor Encoding and SMOTE
, 2023 Fraud detection is a critical task across various domains, requiring accurate identification of fraudulent activities within vast arrays of transactional data.
Çakır, Mert Yılmaz, Şirin, Yahya
core +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Integrated Autoencoder-Level Set Method Outperforms Autoencoder for Novelty Detection [PDF]
, 2022 Novelty detection (ND) has gained attention in many applications for its effectiveness in dealing with imbalanced data. Many ND algorithms have been proposed.
Coyle, Damien, Liu, Shuo
core +1 more source
Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou +4 more
wiley +1 more source
mappl-pldi24-ae/mappl-pldi24-ae: v0.1-beta
<h2>What's Changed</h2> <ul> <li>Add Docker Support by @mappl-pldi24-ae in https://github.com/mappl-pldi24-ae/mappl-pldi24-ae/pull/1</li> <li>Fix typos</li> </ul> <h2>New Contributors</h2> < ...
mappl-pldi24-ae
core +1 more source
Transformer-based autoencoder with ID constraint for unsupervised anomalous sound detection
EURASIP Journal on Audio, Speech, and Music Processing, 2023 Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised learning based methods are two mainstream methods.
Jian Guan +6 more
doaj +1 more source
Cladistics, EarlyView.Abstract Subterranean ecosystems harbour exceptional biodiversity shaped by adaptation to extreme environments, yet remain poorly explored. Cave organisms, restricted to small, isolated populations, are extinction‐prone, making integrative species delimitation essential for biodiversity assessment and conservation.
Dora Hlebec +3 more
wiley +1 more source
mappl-pldi24-ae/mappl-pldi24-ae: v0.2-alpha
<p>[PLDI'24 Artifact] Variable Elimination for an Expressive Probabilistic Programming Language</p> <h2>What's Changed</h2> <ul> <li>Newexamples by @mappl-pldi24-ae in https://github.com/mappl-pldi24-ae/mappl-pldi24-ae/
mappl-pldi24-ae
core +1 more source