Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3586718
Abstract: intelligent fault diagnosis (IFD) plays a crucial role in ensuring the safe operation of industrial machinery and improving production efficiency. However, traditional supervised deep learning methods require a large amount of training data and labels,… read more here.
Keywords: dual contrastive; semi supervised; intelligent fault; fault diagnosis ... See more keywords
Dual Contrastive Learning Network for Graph Clustering.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3244397
Abstract: Graph representation is an important part of graph clustering. Recently, contrastive learning, which maximizes the mutual information between augmented graph views that share the same semantics, has become a popular and powerful paradigm for graph… read more here.
Keywords: network; graph; dual contrastive; graph clustering ... See more keywords
Learning Event Representations for Zero-Shot Detection via Dual-Contrastive Prompting
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12091372
Abstract: Zero-shot event detection aims to involve the automatic discovery and classification of new events within unstructured text. Current zero-shot event detection methods have not considered addressing the problem more effectively from the perspective of improving… read more here.
Keywords: detection; dual contrastive; event representations; zero shot ... See more keywords