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	The Second Workshop on Applied Machine Learning Management.	Dmitri Goldenberg, Chana Ross, Shir Meir Lador, Lin Lee Cheong, Panpan Xu, Elena Sokolova, Amit Mandelbaum, Irina Vasilinetc, Ankit Jain, Amit Weil Modlinger, Saloni Potdar
2023	Privacy in Advertising: Analytics and Modeling.	Badih Ghazi, Ravi Kumar, Pasin Manurangsi
2023	Addressing Bias and Fairness in Machine Learning: A Practical Guide and Hands-on Tutorial.	Rayid Ghani, Kit T. Rodolfa, Pedro Saleiro, Srgio M. Jesus
2023	GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction.	Haoyu Geng, Runzhong Wang, Fei Wu, Junchi Yan
2023	Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations.	Haoyu Geng, Chao Chen, Yixuan He, Gang Zeng, Zhaobing Han, Hua Chai, Junchi Yan
2023	KiL 2023 : 3rd International Workshop on Knowledge-infused Learning.	Manas Gaur, Efthymia Tsamoura, Sarath Sreedharan, Sudip Mittal
2023	Distributed Optimization for Big Data Analytics: Beyond Minimization.	Hongchang Gao, Xinwen Zhang
2023	Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design.	Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Tianbo Peng, Yingce Xia, Liang He, Shufang Xie, Tao Qin, Haiguang Liu, Kun He, Tie-Yan Liu
2023	Binary Embedding-based Retrieval at Tencent.	Yukang Gan, Yixiao Ge, Chang Zhou, Shupeng Su, Zhouchuan Xu, Xuyuan Xu, Quanchao Hui, Xiang Chen, Yexin Wang, Ying Shan
2023	AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases.	Giridhar Ganapavarapu, Sumanta Mukherjee, Natalia Martinez Gil, Kanthi K. Sarpatwar, Amaresh Rajasekharan, Amit Dhurandhar, Vijay Arya, Roman Vaculn
2023	Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling.	Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong
2023	Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-turn Conversations.	Tingchen Fu, Xueliang Zhao, Rui Yan
2023	Dependence and Model Selection in LLP: The Problem of Variants.	Gabriel Franco, Mark Crovella, Giovanni Comarela
2023	ILRoute: A Graph-based Imitation Learning Method to Unveil Riders' Routing Strategies in Food Delivery Service.	Tao Feng, Huan Yan, Huandong Wang, Wenzhen Huang, Yuyang Han, Hongsen Liao, Jinghua Hao, Yong Li
2023	Influence Maximization with Fairness at Scale.	Yuting Feng, Ankitkumar Patel, Bogdan Cautis, Hossein Vahabi
2023	FedMultimodal: A Benchmark for Multimodal Federated Learning.	Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan
2023	A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification.	Kevin Fauvel, Fuxing Chen, Dario Rossi
2023	Trustworthy Recommender Systems: Foundations and Frontiers.	Wenqi Fan, Xiangyu Zhao, Lin Wang, Xiao Chen, Jingtong Gao, Qidong Liu, Shijie Wang
2023	Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance.	Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu
2023	RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment.	Chuyu Fang, Chuan Qin, Qi Zhang, Kaichun Yao, Jingshuai Zhang, Hengshu Zhu, Fuzhen Zhuang, Hui Xiong
2023	Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial Forensics.	Youssef Elmougy, Ling Liu
2023	Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks.	Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C. Uyeda, Meghan A. Balk, Wasila M. Dahdul, Yasin Bakis, Henry L. Bart Jr., Paula M. Mabee, Hilmar Lapp, James P. Balhoff, Caleb Charpentier, David Carlyn, Wei-Lun Chao, Charles V. Stewart, Daniel I. Rubenstein, Tanya Y. Berger-Wolf, Anuj Karpatne
2023	TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting.	Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
2023	Time-to-Event Modeling with Hypernetwork based Hawkes Process.	Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar
2023	Localised Adaptive Spatial-Temporal Graph Neural Network.	Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao

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