Node Dependent Local Smoothing for Scalable Graph Learning

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Deep Learning NDLS
Overview

Node Dependent Local Smoothing for Scalable Graph Learning

Requirements

Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04 (OS)

The PyTorch version we use is torch 1.7.1+cu110. Please refer to the official website -- https://pytorch.org/get-started/locally/ -- for the detailed installation instructions.

To install other requirements:

pip install -r requirements.txt

Training

To train the model(s) in the paper, run this command:

cd src; python train.py --dataset cora/citeseer/pubmed

Please refer to the Appendix for the detailed hyperparameters.

Node Classification Results

  1. Transductive Setting:

    transductive

  2. Inductive Setting:

    inductive

  3. Efficiency Comparison:

    efficiency

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Comments
  • Some Questions

    Some Questions

    Hi wentao! Excellent work!!! Due to my poor capability of math , I raise the following questions for the paper: when a connected graph with the adjacent matrix A without self-loop and using r=0.5(Acap = D{^0.5}AD{^0.5} ) is used, will the Eq. 2 in the paper become : Acap-infinity = sqrt(di)*sqrt(dj)/ (2m + n) ? will the Theorem 3.1. become: (di +1) in the Eq. 6 to di ? will the Theorem 3.2. still be corret? and are there some tips to choose a proper epsilon for a specific task? thank you for reading this issue!

    opened by LIUkhan 3
  • Inductive setting

    Inductive setting

    What is specific training process for inductive setting? If new node (unseen in training stage) comes in the test stage, the adjacency matrix becomes different from the training stage, and LSI value of each node is also different, then wouldn't it be impossible to use the optimized MLP parameter based on the training graph structure??

    opened by sungeun532 0
  • Calculation of local smoothing iteration

    Calculation of local smoothing iteration

    In train.py, when you calculate the LSI, why do you not calculate node's converget state for each node, but calculate 1x(dim of feat) vector "norm_fea_inf" as the same convergent stae for all nodes?

    opened by sungeun532 2
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Wentao Zhang
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