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cs.LG2024
Hybrid FedGraph: An efficient hybrid federated learning algorithm using graph convolutional neural network
Jaeyeon Jang, Diego Klabjan, Veena Mendiratta +1
Federated learning is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server. Most exis…
cs.LG2024
Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit
Fanfei Meng, Lele Zhang, Yu Chen +1
Transformer requires a fixed number of layers and heads which makes them inflexible to the complexity of individual samples and expensive in training and inference. To address this…
cs.LG2024
FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation
Fanfei Meng, Lele Zhang, Yu Chen +1
Federated learning (FL) is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server. The…