Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation-Reference-Cited by-同舟云学术

Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Chen Yankai¹,Guo Huifeng²,Zhang Yingxue²,Ma Chen³,Tang Ruiming²,Li Jingjie²,King Irwin¹

Affiliation:

1. The Chinese University of Hong Kong, Hong Kong, Hong Kong

2. Huawei Noah's Ark Lab, Shenzhen, China

3. City University of Hong Kong, Hong Kong, Hong Kong

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539452

Reference69 articles.

1. Rohan Anil Gabriel Pereyra Alexandre Passos Robert Ormandi George E Dahl and Geoffrey E Hinton. 2018. Large scale distributed neural network training through online distillation. ICLR. Rohan Anil Gabriel Pereyra Alexandre Passos Robert Ormandi George E Dahl and Geoffrey E Hinton. 2018. Large scale distributed neural network training through online distillation. ICLR.

2. Mehdi Bahri Gaétan Bahl and Stefanos Zafeiriou. 2021. Binary Graph Neural Networks. In CVPR. 9492--9501. Mehdi Bahri Gaétan Bahl and Stefanos Zafeiriou. 2021. Binary Graph Neural Networks. In CVPR. 9492--9501.

3. Ron Banner , Itay Hubara , Elad Hoffer , and Daniel Soudry . 2018 . Scalable methods for 8-bit training of neural networks . NeurIPS , Vol. 31 . Ron Banner, Itay Hubara, Elad Hoffer, and Daniel Soudry. 2018. Scalable methods for 8-bit training of neural networks. NeurIPS, Vol. 31.

4. Yoshua Bengio Nicholas Léonard and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv. Yoshua Bengio Nicholas Léonard and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv.

5. Rianne van den Berg Thomas N Kipf and Max Welling. 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263. Rianne van den Berg Thomas N Kipf and Max Welling. 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263.

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