Architecture agnostic federated learning for neural networks
With growing concerns regarding data privacy and rapid increase in data volume, Federated
Learning (FL) has become an important learning paradigm. However, jointly learning a deep …
Learning (FL) has become an important learning paradigm. However, jointly learning a deep …
Efficient and Trustworthy Federated Learning-Based Explainable Anomaly Detection: Challenges, Methods, and Future Directions
Artificial Intelligence (AI) and especially Machine Learning (ML) are the driving energy
behind industrial and technological transformation. With the transition from industry 4.0 to …
behind industrial and technological transformation. With the transition from industry 4.0 to …
Causal inference of multivariate time series in complex industrial systems
X Liang, K Hao, L Chen, X Cai, L Hao - Advanced Engineering Informatics, 2024 - Elsevier
In complex industrial systems, causal inference plays a crucial role in improving production
and tracing faults. The causal inference of industrial systems encompasses two main steps …
and tracing faults. The causal inference of industrial systems encompasses two main steps …
Gain Cell-Based Analog Content Addressable Memory for Dynamic Associative tasks in AI
Analog Content Addressable Memories (aCAMs) have proven useful for associative in-
memory computing applications like Decision Trees, Finite State Machines, and Hyper …
memory computing applications like Decision Trees, Finite State Machines, and Hyper …
[PDF][PDF] 1 Optimization methods and momentum-based deep learning models
TANM NGUYEN - tanmnguyen89.github.io
Deep learning models have been achieving state-of-the-art performance on a wide range of
machine learning tasks including those in computer vision and natural language processing …
machine learning tasks including those in computer vision and natural language processing …