Few-shot Link Prediction in Dynamic Networks-Reference-Cited by-同舟云学术

Few-shot Link Prediction in Dynamic Networks

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
language:
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Author:

Yang Cheng¹,Wang Chunchen²,Lu Yuanfu³,Gong Xumeng⁴,Shi Chuan¹,Wang Wei³,Zhang Xu³

Affiliation:

1. Beijing University of Posts and Telecommunications & Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing, China

2. Beijing University of Posts and Telecommunications & Tencent Inc., Beijing, China

3. Tencent Inc., Beijing, China

4. Beijing University of Posts and Telecommunicationsb, Beijing, China

Funder

the National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498417

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3. Jatin Chauhan , Deepak Nathani , and Manohar Kaul . 2020. Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures. arXiv preprint arXiv:2002.12815 ( 2020 ). Jatin Chauhan, Deepak Nathani, and Manohar Kaul. 2020. Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures. arXiv preprint arXiv:2002.12815 (2020).

4. Aswathy Divakaran and Anuraj Mohan . 2019. Temporal link prediction: a survey. New Generation Computing ( 2019 ), 1--46. Aswathy Divakaran and Anuraj Mohan. 2019. Temporal link prediction: a survey. New Generation Computing (2019), 1--46.

5. Chelsea Finn , Pieter Abbeel , and Sergey Levine . 2017 . Model-agnostic meta-learning for fast adaptation of deep networks . In Proceedings of ICML . 1126--1135 . Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In Proceedings of ICML . 1126--1135.

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