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1. ICDM-2022-TLGCN ICDM-2022-TLGCN Public

   This is the PyTorch implementation for the paper entitled "A Two-Stream Light Graph Convolution Network-based Latent Factor Model for Accurate Cloud Service QoS Estimation", which has been acceppte…

   Python 2

2. TSC-2022-TGLFA TSC-2022-TGLFA Public

   This is the PyTorch implementation for the paper entitled "Two-Stream Graph Convolutional Network- Incorporated Latent Feature Analysis".

   Python 1

3. TSC-2022-TGLFA-Supplementary-File TSC-2022-TGLFA-Supplementary-File Public

   This is the supplementary file for the paper entitled “Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis”. Additional tables and figures are put into this file and cited b…

4. TGLFA TGLFA Public

   This is the supplementary file and PyTorch implementation for the paper entitled “Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis”.

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5. FNAE FNAE Public

   This is the supplementary file for the paper entitled “A Fast Nonnegative Autoencoder-Based Approach to Latent Feature Analysis on High-Dimensional and Incomplete Data”. Additional tables and figur…

6. GLCPN GLCPN Public

   This is the supplementary file, PyTorch implementation, and prepared datasets for the paper entitled “Graph Linear Convolution Pooling for Learning in Incomplete High-Dimensional Data”.