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Found 4 papers, 1 papers with code
A Novel Optimized Asynchronous Federated Learning Framework
How to find a balance between the model performance and the communication cost is a challenge in AFL.
Foreground Object Structure Transfer for Unsupervised Domain Adaptation
In practice, since the label of the target domain is not available, we use the clustering information of the source domain to assign pseudo labels to the target domain samples, and then according to the source domain data prior knowledge guides those positive features to maximum the inter-class distance between different classes and mimimum the intra-class distance.
Deep Fusion Clustering Network
Specifically, in our network, an interdependency learning-based Structure and Attribute Information Fusion (SAIF) module is proposed to explicitly merge the representations learned by an autoencoder and a graph autoencoder for consensus representation learning.
Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA
In this paper, we define the traffic data time singularity ratio in the dropout module and propose a combination prediction method based on the improved long short-term memory neural network and time series autoregressive integrated moving average model (SDLSTM-ARIMA), which is derived from the Recurrent Neural Networks (RNN) model.
