Federated Learning

Beyond Aggregation: Efficient Federated Model Consolidation with Heterogeneity-Adaptive Weights Diffusion
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Beyond Aggregation: Efficient Federated Model Consolidation with Heterogeneity-Adaptive Weights Diffusion
Task-Agnostic Decision Transformer for Multi-Type Agent Control with Federated Split Training
With the rapid advancements in artificial intelligence, the development of knowledgeable and personalized agents has become …
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Task-Agnostic Decision Transformer for Multi-Type Agent Control with Federated Split Training
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer
Federated Learning (FL) has been widely con- cerned for it enables decentralized learning while ensuring data privacy. However, most …
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FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer
Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization
Text summarization is essential for information aggregation and demands large amounts of training data. However, concerns about data …
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A Fair Federated Learning Framework With Reinforcement Learning
Federated learning (FL) is a paradigm where many clients collaboratively train a model under the coordination of a central server, …
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A Nearest Neighbor Under-sampling Strategy for Vertical Federated Learning in Financial Domain
Machine learning techniques have been widely applied in modern financial activities. Participants in the field are aware of the …
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A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy
Currently, the federated graph neural network (GNN) has attracted a lot of attention due to its wide applications in reality without …
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Cali3F: Calibrated Fast Fair Federated Recommendation System
The increasingly stringent regulations on privacy protection have sparked interest in federated learning. As a distributed machine …
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Federated Non-negative Matrix Factorization for Short Texts Topic Modeling with Mutual Information
Non-negative matrix factorization (NMF) based topic modeling is widely used in natural language processing (NLP) to uncover hidden …
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Federated Split BERT for Heterogeneous Text Classification
Pre-trained BERT models have achieved impressive performance in many natural language processing (NLP) tasks. However, in many …
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