Deep neural networks and tabular data: A survey
Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …
numerous critical and computationally demanding applications. On homogeneous datasets …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
Security of federated learning in 6G era: A review on conceptual techniques and software platforms used for research and analysis
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
Towards interpretable federated learning
Federated learning (FL) enables multiple data owners to build machine learning models
collaboratively without exposing their private local data. In order for FL to achieve …
collaboratively without exposing their private local data. In order for FL to achieve …
Flames2graph: An interpretable federated multivariate time series classification framework
Increasing privacy concerns have led to decentralized and federated machine learning
techniques that allow individual clients to consult and train models collaboratively without …
techniques that allow individual clients to consult and train models collaboratively without …
Heart Sound Abnormality Detection From Multi-Institutional Collaboration: Introducing a Federated Learning Framework
Objective: Early diagnosis of cardiovascular diseases is a crucial task in medical practice.
With the application of computer audition in the healthcare field, artificial intelligence (AI) has …
With the application of computer audition in the healthcare field, artificial intelligence (AI) has …
Federated data model-go local, go global and go fusion-in an industry 4.0 context
D Einarson, C Sennersten - Handbook on Federated Learning, 2024 - taylorfrancis.com
To set the main data model further in perspective and focus the authors continue with data
interoperability and data pattern recognition before summarizing the chapter. In terms of …
interoperability and data pattern recognition before summarizing the chapter. In terms of …
Concept-Guided Interpretable Federated Learning
J Yang, G Long - Australasian Joint Conference on Artificial Intelligence, 2023 - Springer
Interpretable federated learning is an emerging challenge to identify explainable
characteristics of each client-specific personalized model in a federated learning system …
characteristics of each client-specific personalized model in a federated learning system …
VFLens: Co-design the Modeling Process for Efficient Vertical Federated Learning via Visualization
As a decentralized training approach, federated learning enables multiple organizations to
jointly train a model without exposing their private data. This work investigates vertical …
jointly train a model without exposing their private data. This work investigates vertical …
Privacy-preserving personal data analysis
C Sun - 2022 - cris.maastrichtuniversity.nl
Ever-increasing amount of data is generated by our citizens and used in our daily life every
single day. These massive amounts of data can be used to improve digital technologies and …
single day. These massive amounts of data can be used to improve digital technologies and …