Conference Paper2025

SSMT: Few-Shot Traffic Forecasting with Single Source Meta-transfer

Kishor Kumar Bhaumik, Minha Kim, Fahim Faisal Niloy, Amin Ahsan Ali, Simon S. Woo

Pattern Recognition

Springer Nature Switzerland, pp. 46-61, ISBN: 9783031781940

  • Sustainable Cities and Communities — Relevance: 60%

Keywords

  • traffic prediction
  • few-shot learning
  • sinusoidal positional encoding
  • intelligent transportation systems
  • meta-learning

CCDS Authors

Kishor Kumar Bhaumik
Kishor Kumar Bhaumik

Kishor Kumar Bhaumik

PhD student

University of California, Riverside

Published at

WACV, Pattern Recognition

Research Interests

Machine Learning

Fahim Faisal Niloy
Fahim Faisal Niloy

Fahim Faisal Niloy

  • Research Assistant, CCDS

PhD Student

University of California Riverside

Published at

WACV, ICPR, ICIP, Pattern Recognition

Research Interests

Machine Learning

Amin Ahsan Ali, PhD
Amin Ahsan Ali, PhD

Amin Ahsan Ali, PhD

  • Director, AI/ML Wing

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Research Interests

Artificial Intelligence, Machine Learning

References

  1. 1.Bing Yu, Haoteng Yin, Zhanxing Zhu. (2018). Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting. , 3634–3640[10.24963/ijcai.2018/505]
  2. 2.Ling Zhao, Yujiao Song, Chao Zhang, Yu Liu, Pu Wang, Tao Lin, Min Deng, Haifeng Li. (2019). T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 21(9), 3848–3858[10.1109/tits.2019.2935152]
  3. 3.Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang. (2019). Graph WaveNet for Deep Spatial-Temporal Graph Modeling. , 1907–1913[10.24963/ijcai.2019/264]
  4. 4.Dong Gong, Lingqiao Liu, Vuong Le, Budhaditya Saha, Moussa Reda Mansour, Svetha Venkatesh, Anton Van Den Hengel. (2019). Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection. , 1705–1714[10.1109/iccv.2019.00179]
  5. 5.Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap. (2016). Meta-learning with memory-augmented neural networks. International Conference on Machine Learning, 1842–1850
  6. 6.Hyunjong Park, Jongyoun Noh, Bumsub Ham. (2020). Learning Memory-Guided Normality for Anomaly Detection. , 14360–14369[10.1109/cvpr42600.2020.01438]
  7. 7.Mohammed S. Ahmed, A R Cook. (1979). ANALYSIS OF FREEWAY TRAFFIC TIME-SERIES DATA BY USING BOX-JENKINS TECHNIQUES. Transportation Research Record Journal of the Transportation Research Board(722)
  8. 8.Shengnan Guo, Youfang Lin, Huaiyu Wan, Xiucheng Li, Gao Cong. (2021). Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting. IEEE Transactions on Knowledge and Data Engineering, 34(11), 5415–5428[10.1109/tkde.2021.3056502]
  9. 9.Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang. (2019). Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning. , 1720–1730[10.1145/3292500.3330884]
  10. 10.Wen Zhang, Lingfei Deng, Lei Zhang, Dongrui Wu. (2022). A Survey on Negative Transfer. IEEE/CAA Journal of Automatica Sinica, 10(2), 305–329[10.1109/jas.2022.106004]
  11. 11.Lei Bai, Lina Yao, Salil S. Kanhere, Xianzhi Wang, Quan Z. Sheng. (2019). STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting. , 1981–1987[10.24963/ijcai.2019/274]
  12. 12.Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen, Yasumasa Kobayashi, Xuan Song, Shintaro Fukushima, Toyotaro Suzumura. (2023). Spatio-Temporal Meta-Graph Learning for Traffic Forecasting. Proceedings of the AAAI Conference on Artificial Intelligence, 37(7), 8078–8086[10.1609/aaai.v37i7.25976]
  13. 13.Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li. (2019). Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. , 2181–2191[10.1145/3308558.3313577]
  14. 14.Yuntao Du, Jindong Wang, Wenjie Feng, Sinno Pan, Tao Qin, Renjun Xu, Chongjun Wang. (2021). AdaRNN. , 402–411[10.1145/3459637.3482315]
  15. 15.Leye Wang, Xu Geng, Xiaojuan Ma, Feng Liu, Qiang Yang. (2019). Cross-City Transfer Learning for Deep Spatio-Temporal Prediction. , 1893–1899[10.24963/ijcai.2019/262]
  16. 16.Bin Lu, Xiaoying Gan, Haiming Jin, Luoyi Fu, Haisong Zhang. (2020). Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting. , 1025–1034[10.1145/3340531.3411894]
  17. 17.Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang. (2022). Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 1162–1172[10.1145/3534678.3539281]
  18. 18.Ankith Jain Rakesh Kumar, Bir Bhanu. (2021). Micro-Expression Classification based on Landmark Relations with Graph Attention Convolutional Network. , 1511–1520[10.1109/cvprw53098.2021.00167]
  19. 19.Yilun Jin, Kai Chen, Qiang Yang. (2022). Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 731–741[10.1145/3534678.3539250]
  20. 20.Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex Liu. (2022). Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2362–2368[10.24963/ijcai.2022/328]
  21. 21.Zhanyu Liu, Guanjie Zheng, Yanwei Yu. (2023). Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank. , 1451–1460[10.1145/3583780.3614829]
  22. 22.Tien Huu Do, Evaggelia Tsiligianni, Xuening Qin, Jelle Hofman, Valerio Panzica La Manna, Wilfried Philips, Nikos Deligiannis. (2020). Graph-Deep-Learning-Based Inference of Fine-Grained Air Quality From Mobile IoT Sensors. IEEE Internet of Things Journal, 7(9), 8943–8955[10.1109/jiot.2020.2999446]
  23. 23.Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo. (2022). STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. 2022 IEEE International Conference on Data Mining (ICDM), 743–752[10.1109/icdm54844.2022.00085]
  24. 24.Finn, Chelsea, Abbeel, Pieter, Levine, Sergey. (2017). Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks. arXiv (Cornell University)[10.48550/arxiv.1703.03400]
  25. 25.Cini, Andrea, Marisca, Ivan, Zambon, Daniele, Alippi, Cesare. (2023). Taming Local Effects in Graph-based Spatiotemporal Forecasting. arXiv (Cornell University)[10.48550/arxiv.2302.04071]