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	Grace: Graph Self-Distillation and Completion to Mitigate Degree-Related Biases.	Hui Xu, Liyao Xiang, Femke Huang, Yuting Weng, Ruijie Xu, Xinbing Wang, Chenghu Zhou
2023	Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN).	Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi
2023	PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay.	Jun Zhou, Yang Bao, Daohong Jian, Hua Wu
2023	Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications.	Min Zhou, Menglin Yang, Bo Xiong, Hui Xiong, Irwin King
2023	Generative Flow Network for Listwise Recommendation.	Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai
2023	PlanRanker: Towards Personalized Ranking of Train Transfer Plans.	Jia Xu, Wanjie Tao, Zulong Chen, Jin Huang, Huihui Liu, Hong Wen, Shenghua Ni, Qun Dai, Yu Gu
2023	Capacity Constrained Influence Maximization in Social Networks.	Shiqi Zhang, Yiqian Huang, Jiachen Sun, Wenqing Lin, Xiaokui Xiao, Bo Tang
2023	Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM.	Hyunsung Kim, Han-Jun Choi, Changjo Kim, Jinsung Yoon, Sang-Ki Ko
2023	Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization.	Kaixuan Chen, Shunyu Liu, Tongtian Zhu, Ji Qiao, Yun Su, Yingjie Tian, Tongya Zheng, Haofei Zhang, Zunlei Feng, Jingwen Ye, Mingli Song
2023	Constrained Social Community Recommendation.	Xingyi Zhang, Shuliang Xu, Wenqing Lin, Sibo Wang
2023	One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data.	Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
2023	Internal Logical Induction for Pixel-Symbolic Reinforcement Learning.	Jiacheng Xu, Chao Chen, Fuxiang Zhang, Lei Yuan, Zongzhang Zhang, Yang Yu
2023	Generalizing Graph ODE for Learning Complex System Dynamics across Environments.	Zijie Huang, Yizhou Sun, Wei Wang
2023	TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter.	Xinyang Zhang, Yury Malkov, Omar Florez, Serim Park, Brian McWilliams, Jiawei Han, Ahmed El-Kishky
2023	How does the Memorization of Neural Networks Impact Adversarial Robust Models?	Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang
2023	Learning for Counterfactual Fairness from Observational Data.	Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
2023	Source-Free Domain Adaptation with Temporal Imputation for Time Series Data.	Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
2023	CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems.	Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun
2023	The 3rd Workshop on Graph Learning Benchmarks (GLB 2023).	Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
2023	IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics.	Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Ke-Bin Fan, De-Chuan Zhan, Yang Yang
2023	Sketch-Based Anomaly Detection in Streaming Graphs.	Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi
2023	Finding Favourite Tuples on Data Streams with Provably Few Comparisons.	Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
2023	XAI for Predictive Maintenance.	Joo Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso
2023	Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay.	Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
2023	Prescriptive PCA: Dimensionality Reduction for Two-stage Stochastic Optimization.	Long He, Ho-Yin Mak

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