ACM International Conference on Knowledge Discovery and Data Mining

KDD

CORE rank

CORE rank (raw)

Acceptance rate

20.0% (2024 research track)

Fields of research

Data Management and Data Science · Machine Learning

Papers indexed

8,232

1994–2026

Best Machine Learning conferences Best Data Science and Information Retrieval conferences

Papers per year

1994844 peak2026

Most published authors

KDD papers

8,232 records sourced from DBLP. Search titles, filter by year, sort by recency.

Year	Title	Authors
2023	A Collaborative Transfer Learning Framework for Cross-domain Recommendation.	Wei Zhang, Pengye Zhang, Bo Zhang, Xingxing Wang, Dong Wang
2023	AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning.	Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
2023	DM-PFL: Hitchhiking Generic Federated Learning for Efficient Shift-Robust Personalization.	Wenhao Zhang, Zimu Zhou, Yansheng Wang, Yongxin Tong
2023	GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes.	Jian Zhang, Da Zheng, Xiang Song, Theodore Vasiloudis, Israt Nisa, Jim Lu
2023	Debiasing Recommendation by Learning Identifiable Latent Confounders.	Qing Zhang, Xiaoying Zhang, Yang Liu, Hongning Wang, Min Gao, Jiheng Zhang, Ruocheng Guo
2023	Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series.	Jiawen Zhang, Shun Zheng, Wei Cao, Jiang Bian, Jia Li
2023	Rumor Detection with Diverse Counterfactual Evidence.	Kaiwei Zhang, Junchi Yu, Haichao Shi, Jian Liang, Xiaoyu Zhang
2023	Local Boosting for Weakly-Supervised Learning.	Rongzhi Zhang, Yue Yu, Jiaming Shen, Xiquan Cui, Chao Zhang
2023	Towards Disentangling Relevance and Bias in Unbiased Learning to Rank.	Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork
2023	Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree.	Delvin Ce Zhang, Rex Ying, Hady W. Lauw
2023	Efficient Approximation Algorithms for Spanning Centrality.	Shiqi Zhang, Renchi Yang, Jing Tang, Xiaokui Xiao, Bo Tang
2023	RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery.	Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang
2023	Efficient Single-Source SimRank Query by Path Aggregation.	Mingxi Zhang, Yanghua Xiao, Wei Wang
2023	Modeling Dual Period-Varying Preferences for Takeaway Recommendation.	Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu
2023	Domain-Specific Risk Minimization for Domain Generalization.	Yifan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, Xing Xie
2023	Adaptive Disentangled Transformer for Sequential Recommendation.	Yipeng Zhang, Xin Wang, Hong Chen, Wenwu Zhu
2023	Doubly Robust AUC Optimization against Noisy and Adversarial Samples.	Chenkang Zhang, Wanli Shi, Lei Luo, Bin Gu
2023	A Personalized Automated Bidding Framework for Fairness-aware Online Advertising.	Haoqi Zhang, Lvyin Niu, Zhenzhe Zheng, Zhilin Zhang, Shan Gu, Fan Wu, Chuan Yu, Jian Xu, Guihai Chen, Bo Zheng
2023	MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation.	Jiaxing Zhang, Dongsheng Luo, Hua Wei
2023	Towards a Generic Framework for Mechanism-guided Deep Learning for Manufacturing Applications.	Hanbo Zhang, Jiangxin Li, Shen Liang, Peng Wang, Themis Palpanas, Chen Wang, Wei Wang, Haoxuan Zhou, Jianwei Song, Wen Lu
2023	Deep Transfer Learning for City-scale Cellular Traffic Generation through Urban Knowledge Graph.	Shiyuan Zhang, Tong Li, Shuodi Hui, Guangyu Li, Yanping Liang, Li Yu, Depeng Jin, Yong Li
2023	Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers.	Yu Zhang, Bowen Jin, Xiusi Chen, Yanzhen Shen, Yunyi Zhang, Yu Meng, Jiawei Han
2023	A Study of Situational Reasoning for Traffic Understanding.	Jiarui Zhang, Filip Ilievski, Kaixin Ma, Aravinda Kollaa, Jonathan Francis, Alessandro Oltramari
2023	FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy.	Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan
2023	Hierarchical Invariant Learning for Domain Generalization Recommendation.	Zeyu Zhang, Heyang Gao, Hao Yang, Xu Chen

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