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
2020	Recurrent Halting Chain for Early Multi-label Classification.	Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner
2020	ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction.	Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee
2020	Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data.	Qianyue Hao, Lin Chen, Fengli Xu, Yong Li
2020	Meta-Learning for Query Conceptualization at Web Scale.	Fred X. Han, Di Niu, Haolan Chen, Weidong Guo, Shengli Yan, Bowei Long
2020	Learning to Score Economic Development from Satellite Imagery.	Sungwon Han, Donghyun Ahn, Sungwon Park, Jeasurk Yang, Susang Lee, Jihee Kim, Hyunjoo Yang, Sangyoon Park, Meeyoung Cha
2020	WhyFlow: Explaining Errors in Data Flows Interactively.	Maeda F. Hanafi, Azza Abouzied, Marina Danilevsky, Yunyao Li
2020	Preserving Integrity in Online Social Media.	Alon Y. Halevy
2020	Improving Deep Learning for Airbnb Search.	Malay Haldar, Prashant Ramanathan, Tyler Sax, Mustafa Abdool, Lanbo Zhang, Aamir Mansawala, Shulin Yang, Bradley C. Turnbull, Junshuo Liao
2020	Grale: Designing Networks for Graph Learning.	Jonathan Halcrow, Alexandru Mosoi, Sam Ruth, Bryan Perozzi
2020	Image and Video Understanding for Recommendation and Spam Detection Systems.	Aman Gupta, Sirjan Kafle, Di Wen, Dylan Wang, Sumit Srivastava, Suhit Sinha, Nikita Gupta, Bharat Jain, Ananth Sankar, Liang Zhang
2020	Interpretable Deep Graph Generation with Node-edge Co-disentanglement.	Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye
2020	RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift.	Lan-Zhe Guo, Zhi Zhou, Yufeng Li
2020	Debiasing Grid-based Product Search in E-commerce.	Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong, Huan Liu
2020	Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data.	Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang
2020	Sliding Sketches: A Framework using Time Zones for Data Stream Processing in Sliding Windows.	Xiangyang Gou, Long He, Yinda Zhang, Ke Wang, Xilai Liu, Tong Yang, Yi Wang, Bin Cui
2020	Neural Structured Learning: Training Neural Networks with Structured Signals.	Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu
2020	A Geometric Approach to Predicting Bounds of Downstream Model Performance.	Brian J. Goode, Debanjan Datta
2020	OptMatch: Optimized Matchmaking via Modeling the High-Order Interactions on the Arena.	Linxia Gong, Xiaochuan Feng, Dezhi Ye, Hao Li, Runze Wu, Jianrong Tao, Changjie Fan, Peng Cui
2020	Keynote Speaker: Yolanda Gil.	Yolanda Gil
2020	Multimodal Machine Learning for Video and Image Analysis.	Shalini Ghosh
2020	Data-driven Simulation and Optimization for Covid-19 Exit Strategies.	Salah Ghamizi, Renaud Rwemalika, Maxime Cordy, Lisa Veiber, Tegawend F. Bissyand, Mike Papadakis, Jacques Klein, Yves Le Traon
2020	Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation.	Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Klaus Mueller
2020	Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning.	Timnit Gebru
2020	COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching.	Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun
2020	Kronecker Attention Networks.	Hongyang Gao, Zhengyang Wang, Shuiwang Ji

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