ERAS

The code for our paper ["Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding"], which has been accepted by ICDE 2021.

Readers are welcomed to fork this repository to reproduce the experiments and follow our work. Please kindly cite our paper

@inproceedings{di2021eras,
  title={Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding},
  author={Shimin DI, Quanming YAO, Yongqi ZHANG, and Lei CHEN},
  booktitle={2021 IEEE 37th International Conference on Data Engineering (ICDE)},
  pages={},
  year={2021},
  organization={IEEE}
}

Instructions

For the sake of ease, a quick instruction is given for readers to reproduce the whole process. Note that the programs are tested on Linux(Ubuntu release 16.04), Python 3.7 from Anaconda 4.5.11.

Install PyTorch (>0.4.0)

conda install pytorch -c pytorch

Search and train the searched scoring functions from scratch

python one-shot-search/evaluate.py

Related AutoML papers (ML Research group in 4Paradigm)

• Searching to Sparsify Tensor Decomposition for N-ary Relational Data. Webconf 2021 paper, code
• Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding. NeurIPS 2020 paper, code
• AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. ICDE 2020 paper, code
• Simple and Automated Negative Sampling for Knowledge Graph Embedding. ICDE 2019 paper, code