2022 Proceeding- General Chairs:
- Aidong Zhang,
- Huzefa Rangwala
It is our great pleasure to welcome you back in person after a 2-year hiatus to the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2022), which is held between August 14th and 18th, 2022 at the Walter E. Washington Convention Center in Washington, DC, USA. This year's KDD continues its tradition of being the premier forum for presentation of research results and experience reports on leading edge issues of data science, machine learning, big data and artificial intelligence. The KDD 2022 program promises to be the most robust and diverse to date, with keynote presentations, industry-led sessions, workshops, and tutorials spanning a wide range of topics - from data-driven humanitarian mapping and applied data science in healthcare to the uses of artificial intelligence (AI) for climate mitigation and decision intelligence for online marketplaces.
Cited By
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Han D, Yan M, Ye X and Fan D (2024). Characterizing and Understanding HGNN Training on GPUs, ACM Transactions on Architecture and Code Optimization, 10.1145/3703356
- Rong C, Ding J and Li Y (2024). An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques, ACM Computing Surveys, 0:0
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Xie Y, Zhang H and Babar M (2024). LogSD: Detecting Anomalies from System Logs through Self-Supervised Learning and Frequency-Based Masking, Proceedings of the ACM on Software Engineering, 10.1145/3660800, 1:FSE, (2098-2120), Online publication date: 12-Jul-2024.
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Wang X, Xiao H, Xing Q, Kolivand H and Nayyar A (2023). Contrastive learning enhanced by transformer block for time series forecasting Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 10.1117/12.3012295, 9781510672505, (119)
- Li X, Wu Z, Zhang W, Zhu Y, Li R and Wang G (2023). FedGTA: Topology-Aware Averaging for Federated Graph Learning, Proceedings of the VLDB Endowment, 17:1, (41-50), Online publication date: 1-Sep-2023.
- Fu D, Bao W, Maciejewski R, Tong H and He J (2023). Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey, ACM SIGKDD Explorations Newsletter, 25:1, (54-72), Online publication date: 22-Jun-2023.
- Gerogiannis G, Yesil S, Lenadora D, Cao D, Mendis C and Torrellas J SPADE: A Flexible and Scalable Accelerator for SpMM and SDDMM Proceedings of the 50th Annual International Symposium on Computer Architecture, (1-15)
- Zhang J, Jin D and Li Y Mirage Proceedings of the 30th International Conference on Advances in Geographic Information Systems, (1-4)
- Ge Y, Liu S, Fu Z, Tan J, Li Z, Xu S, Li Y, Xian Y and Zhang Y A Survey on Trustworthy Recommender Systems, ACM Transactions on Recommender Systems, 0:0