Network-Wide Traffic States Imputation Using Self-interested Coalitional Learning-Reference-Cited by-同舟云学术

Network-Wide Traffic States Imputation Using Self-interested Coalitional Learning

Published:2021-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
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Author:

qin Huiling¹,Zhan Xianyuan²,Li Yuanxun³,Yang Xiaodu⁴,Zheng Yu⁵

Affiliation:

1. Xidian University & JD Technology, Xi'an, China

2. JD Intelligent Cities Research, Beijing, China

3. Sun Yat-sen University, Guangzhou, China

4. Southwest Jiaotong University, Chengdu, China

5. Xidian University & JD Technology, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3447548.3467424

Reference32 articles.

1. City-scale traffic estimation from a roving sensor network

2. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in neural information processing systems. 3844--3852. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in neural information processing systems. 3844--3852.

3. Review: A gentle introduction to imputation of missing values

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