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08/22/2023
Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models
Multimodal data, which can comprehensively perceive and recognize the ph...
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08/07/2023
The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Transformers
Federated learning (FL) addresses data privacy concerns by enabling coll...
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07/01/2023
Hierarchical Federated Learning Incentivization for Gas Usage Estimation
Accurately estimating gas usage is essential for the efficient functioni...
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02/22/2023
Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout
Artificial intelligence (AI)-empowered industrial fault diagnostics is i...
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11/17/2022
Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery
Intelligent fault diagnosis is essential to safe operation of machinery....
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03/08/2022
LSTMSPLIT: Effective SPLIT Learning based LSTM on Sequential Time-Series Data
Federated learning (FL) and split learning (SL) are the two popular dist...
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08/06/2020
A Survey of Smart Contract Formal Specification and Verification
A smart contract is a computer program which allows users to define and ...
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05/25/2020
Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning
Countries across the globe have been pushing strict regulations on the p...
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03/17/2020