Towards a deep learning approach for IoT attack detection based on a new generative adversarial network architecture and gated recurrent unit
As the use of Internet of Things (IoT) devices has increased rapidly in the last few years, a
major challenge is the security of these devices. Machine learning models can adapt to …
major challenge is the security of these devices. Machine learning models can adapt to …
CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis
Generative adversarial networks (GANs) have drawn considerable attention in recent years
for their proven capability in generating synthetic data which can be utilised for multiple …
for their proven capability in generating synthetic data which can be utilised for multiple …
Super-Resolution Reconstruction of Particleboard Images Based on Improved SRGAN
W Yu, H Zhou, Y Liu, Y Yang, Y Shen - Forests, 2023 - mdpi.com
As an important forest product, particleboard can greatly save forestry resources and
promote low-carbon development by reusing wood processing residues. The size of the …
promote low-carbon development by reusing wood processing residues. The size of the …
A Learnable Discrete-Prior Fusion Autoencoder with Contrastive Learning for Tabular Data Synthesis
R Zhang, Y Lou, D Xu, Y Cao, H Wang… - Proceedings of the AAAI …, 2024 - ojs.aaai.org
The actual collection of tabular data for sharing involves confidentiality and privacy
constraints, leaving the potential risks of machine learning for interventional data analysis …
constraints, leaving the potential risks of machine learning for interventional data analysis …
Poisoning the Competition: Fake Gradient Attacks on Distributed Generative Adversarial Networks
Generative Adversarial Networks (GANs) have gained significant attentions due to their
powerful generative abilities. However, the requirements for data privacy protection and data …
powerful generative abilities. However, the requirements for data privacy protection and data …
P-TA: Using Proximal Policy Optimization to Enhance Tabular Data Augmentation via Large Language Models
A multitude of industries depend on accurate and reasonable tabular data augmentation for
their business processes. Contemporary methodologies in generating tabular data revolve …
their business processes. Contemporary methodologies in generating tabular data revolve …
LDGAN: Latent Determined Ensemble Helps Removing IID Data Assumption and Cross-node Sampling in Distributed GANs
W Wang, Z Wu, X Xiang, Y Li - 2022 26th International …, 2022 - ieeexplore.ieee.org
Generative Adversarial Networks (GANs) have received a lot of attention due to their
powerful generative ability, and many related studies have been carried out. Among them …
powerful generative ability, and many related studies have been carried out. Among them …
FakeDB: Generating Fake Synthetic Databases
Health care providers may wish to share limited information with researchers. Manufacturing
companies may want to share some but not all data with regulators or partners. Since the …
companies may want to share some but not all data with regulators or partners. Since the …
A Psycholinguistics-Inspired Method to Counter IP Theft using Fake Documents
Intellectual property (IP) theft is a growing problem. We build on prior work to deter IP theft by
generating n fake versions of a technical document so that a thief has to expend time and …
generating n fake versions of a technical document so that a thief has to expend time and …
SDWD: Style Diversity Weighted Distance Evaluates the Intra-Class Data Diversity of Distributed GANs
W Wang, Z Wu, M Zhang, Y Li - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Due to the distributed storage of massive data, efficient deployment of Generative
Adversarial Networks (GANs) in distributed scenarios has become a hot topic. This paper …
Adversarial Networks (GANs) in distributed scenarios has become a hot topic. This paper …