Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training-Reference-Cited by-同舟云学术

Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Liu Fan¹^ORCID,Zhang Weijia¹^ORCID,Liu Hao²^ORCID

Affiliation:

1. The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

2. The Hong Kong University of Science and Technology (Guangzhou) & The Hong Kong University of Science and Technology, Guangzhou, China

Funder

Guangzhou Science and Technology Plan Guangzhou-HKUST(GZ) Joint Project

Foshan HKUST Projects

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599492

Reference42 articles.

1. Adversarially Robust Submodular Maximization under Knapsack Constraints

2. Jinghui Chen and Quanquan Gu . 2020 . RayS: A Ray Searching Method for Hard-label Adversarial Attack. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , Virtual Event, CA, USA , August 23-27, 2020, Rajesh Gupta, Yan Liu, Jiliang Tang, and B. Aditya Prakash (Eds.). ACM, 1739--1747. Jinghui Chen and Quanquan Gu. 2020. RayS: A Ray Searching Method for Hard-label Adversarial Attack. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020, Rajesh Gupta, Yan Liu, Jiliang Tang, and B. Aditya Prakash (Eds.). ACM, 1739--1747.

3. Adversarial distributional training for robust deep learning;Dong Yinpeng;Advances in Neural Information Processing Systems,2020

4. Yinpeng Dong , Ke Xu , Xiao Yang , Tianyu Pang , Zhijie Deng , Hang Su , and Jun Zhu . 2022 . Exploring Memorization in Adversarial Training. In The Tenth International Conference on Learning Representations, ICLR 2022 , Virtual Event , April 25-29, 2022. OpenReview.net. Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, and Jun Zhu. 2022. Exploring Memorization in Adversarial Training. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022. OpenReview.net.

5. Ziquan Fang , Yuntao Du , Xinjun Zhu , Danlei Hu , Lu Chen , Yunjun Gao , and Christian S. Jensen . 2022 . Spatio-Temporal Trajectory Similarity Learning in Road Networks. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , Washington, DC, USA, August 14 - 18 , 2022 , Aidong Zhang and Huzefa Rangwala (Eds.). ACM, 347--356. Ziquan Fang, Yuntao Du, Xinjun Zhu, Danlei Hu, Lu Chen, Yunjun Gao, and Christian S. Jensen. 2022. Spatio-Temporal Trajectory Similarity Learning in Road Networks. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022, Aidong Zhang and Huzefa Rangwala (Eds.). ACM, 347--356.

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