KDD

Repeat-Aware Neighbor Sampling for Dynamic Graph Learning

Tao Zou, Yuhao Mao, Junchen Ye, Bowen Du

Comments Accepted by KDD 2024, Research Track

CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control

Jingqing Ruan, Ziyue Li, Hua Wei, Haoyuan Jiang, Jiaming Lu, Xuantang Xiong, Hangyu Mao, Rui Zhao

Comments Accepted by KDD 2024

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems

Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang

Comments Accepted to KDD 2024

OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining

Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, Jie Tang

Comments KDD'24, 9 pages, 5 appendix pages

Journal ref Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), August 25--29, 2024, Barcelona, Spain

Improving Conversational Recommendation Systems via Counterfactual Data Simulation

Xiaolei Wang, Kun Zhou, Xinyu Tang, Wayne Xin Zhao, Fan Pan, Zhao Cao, Ji-Rong Wen

Comments Accepted by KDD 2023. Code: https://github.com/RUCAIBox/CFCRS

Self-Explainable Temporal Graph Networks based on Graph Information Bottleneck

Sangwoo Seo, Sungwon Kim, Jihyeong Jung, Yoonho Lee, Chanyoung Park

Comments KDD 2024

Influence Maximization via Graph Neural Bandits

Yuting Feng, Vincent Y. F. Tan, Bogdan Cautis

Comments To appear at the 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)

Scalable Rule Lists Learning with Sampling

Leonardo Pellegrina, Fabio Vandin

Comments Accepted to KDD 2024

Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model

Jiang-Xin Shi, Chi Zhang, Tong Wei, Yu-Feng Li

Comments Accepted by KDD 2024

The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs

Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang

Comments KDD 2024

RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes

Xiaoshan Yu, Chuan Qin, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu, Xingyi Zhang

Comments Accepted by KDD 2024. 12 pages

Top-Down Bayesian Posterior Sampling for Sum-Product Networks

Soma Yokoi, Issei Sato

Comments KDD 2024

Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask

Jingyu Xiao, Zhiyao Xu, Qingsong Zou, Qing Li, Dan Zhao, Dong Fang, Ruoyu Li, Wenxin Tang, Kang Li, Xudong Zuo, Penghui Hu, Yong Jiang, Zixuan Weng, Michael R. Lyv

Comments KDD 2024

STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning

Wei Shao, Yufan Kang, Ziyan Peng, Xiao Xiao, Lei Wang, Yuhui Yang, Flora D Salim

Comments Accepted paper in KDD 2024

Foundation Models for Time Series Analysis: A Tutorial and Survey

Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen

Comments In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'24)

Effective Generation of Feasible Solutions for Integer Programming via Guided Diffusion

Hao Zeng, Jiaqi Wang, Avirup Das, Junying He, Kunpeng Han, Haoyuan Hu, Mingfei Sun

Comments Accepted to SIGKDD 2024

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning

Yi Liu, Cong Wang, Xingliang Yuan

Comments In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD' 24), August 25-29, 2024, Barcelona, Spain

FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction

Muhao Xu, Zhenfeng Zhu, Youru Li, Shuai Zheng, Yawei Zhao, Kunlun He, Yao Zhao

Comments Accepted by KDD 2024 (Research Track)

Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling

Siwei Zhang, Xi Chen, Yun Xiong, Xixi Wu, Yao Zhang, Yongrui Fu, Yinglong Zhao, Jiawei Zhang

Comments KDD'2024 Research Track Paper

AIM: Attributing, Interpreting, Mitigating Data Unfairness

Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik Hamann, Hanghang Tong

Comments 12 pages, 6 figures, accepted by ACM SIGKDD 2024. Webpage: https://github.com/ZhiningLiu1998/AIM

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark

Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma

Comments KDD ADS 2024

Generative Pretrained Hierarchical Transformer for Time Series Forecasting

Zhiding Liu, Jiqian Yang, Mingyue Cheng, Yucong Luo, Zhi Li

Comments Accepted by KDD'24 Research Track

GPFedRec: Graph-guided Personalization for Federated Recommendation

Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijjian Zhang, Peng Yan, Bo Yang

Comments Accepted as a regular paper of KDD'24

SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning

Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong

Comments Accepted by KDD 2024

Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction

Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao

Comments Accepted by KDD 2024

An Open and Large-Scale Dataset for Multi-Modal Climate Change-aware Crop Yield Predictions

Fudong Lin, Kaleb Guillot, Summer Crawford, Yihe Zhang, Xu Yuan, Nian-Feng Tzeng

Comments 13 pages

Journal ref KDD 2024 ADS track

Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask

Zineb Senane, Lele Cao, Valentin Leonhard Buchner, Yusuke Tashiro, Lei You, Pawel Herman, Mats Nordahl, Ruibo Tu, Vilhelm von Ehrenheim

Comments Published as a full paper by KDD 2024 Research Track (12 pages as main paper and 11 pages as appendix). Source code available at https://github.com/llcresearch/TSDE

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models

Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen

Comments accepted by KDD'24 research track. 21 pages, 10 figures, 8 tables

RLTP: Reinforcement Learning to Pace for Delayed Impression Modeling in Preloaded Ads

Penghui Wei, Yongqiang Chen, Shaoguo Liu, Liang Wang, Bo Zheng

Comments KDD 2023 (Applied Data Science Track). The first two authors contributed equally

Spuriousness-Aware Meta-Learning for Learning Robust Classifiers

Guangtao Zheng, Wenqian Ye, Aidong Zhang

Comments Accepted to KDD 2024