3 accepted papers
"Federated Learning (FL) provides a framework for collaborative training of deep learning models while preserving data privacy by avoiding sharing the training data. However, recent studies have shown that a malicious server can reconstruct training data from the shared gradients of traditional neur…
Conditional random fields (CRFs), a particular type of graph neural networks (GNNs), can be used to make structured predictions in machine learning, with various applications from image processing and natural language processing to recommender systems. CRFs refine the prediction of a sample by takin…
The huge number of parameters of deep neural network makes it difficult to deploy on embedded devices with limited hardware, computation, storage and energy resources. In this paper, we shall propose a log-sum minimization approach to prune a trained network layer by layer thereby improving the netw…