Node Dependent Local Smoothing for Scalable Graph Learning
Authors: Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin CUI
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate that NDLS enjoys high accuracy state-of-the-art performance on node classifications tasks, flexibility can be incorporated with any models, scalability and efficiency can support large scale graphs with fast training. |
| Researcher Affiliation | Collaboration | 1School of CS, Peking University 2Tencent Inc. 3 Key Lab of High Confidence Software Technologies, Peking University 4Institute of Computational Social Science, Peking University (Qingdao), China |
| Pseudocode | No | No explicit pseudocode or algorithm blocks were found in the paper. |
| Open Source Code | No | The paper does not provide a statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | We conduct the experiments on (1) six publicly partitioned datasets, including four citation networks (Citeseer, Cora, Pub Med, and ogbn-papers100M) in [15, 13] and two social networks (Flickr and Reddit) in [32], and (2) one short-form video recommendation graph (Industry) from our industrial cooperative enterprise. The dataset statistics are shown in Table 2 and more details about these datasets can be found in Appendix A.3. |
| Dataset Splits | Yes | Table 2: Overview of datasets and task types (T/I represents Transductive/Inductive). Dataset #Nodes #Features #Edges #Classes #Train/Val/Test Type Description ... Cora 2,708 1,433 5,429 7 140/500/1,000 T citation network |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU/CPU models or memory specifications used for running the experiments. |
| Software Dependencies | No | The paper mentions "Open Box [19]" for hyper-parameter tuning, but does not provide specific version numbers for this or any other software libraries or dependencies used. |
| Experiment Setup | Yes | The hyper-parameters of baselines are tuned by Open Box [19] or set according to the original paper if available. Please refer to Appendix A.5 for more details. |