6 papers
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…
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…
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…
Optimizing the Passenger Flow for Airport Security Check
Yuxin Wang, Fanfei Meng, Xiaotian Wang +1
Due to the necessary security for the airport and flight, passengers are required to have strict security check before getting aboard. However, there are frequent complaints of was…
Joint Detection Algorithm for Multiple Cognitive Users in Spectrum Sensing
Fanfei Meng, Yuxin Wang, Lele Zhang +1
Spectrum sensing technology is a crucial aspect of modern communication technology, serving as one of the essential techniques for efficiently utilizing scarce information resource…
Sentiment analysis with adaptive multi-head attention in Transformer
Fanfei Meng, Chen-Ao Wang
We propose a novel framework based on the attention mechanism to identify the sentiment of a movie review document. Previous efforts on deep neural networks with attention mechanis…