KDD

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

HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning

Zhuoning Guo, Duanyi Yao, Qiang Yang, Hao Liu

Comments Accepted by SIGKDD 2024

ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising

Ruize Wang, Hui Xu, Ying Cheng, Qi He, Xing Zhou, Rui Feng, Wei Xu, Lei Huang, Jie Jiang

Comments Accepted to KDD 2024

Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data

Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield

Comments Accepted by ACM SIGKDD 2024

DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation

Kairui Fu, Shengyu Zhang, Zheqi Lv, Jingyuan Chen, Jiwei Li

Comments Accepted by KDD 2024

Choosing a Proxy Metric from Past Experiments

Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky

Comments To appear in KDD 2024

TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data

Ziyang Zhang, Hejie Cui, Ran Xu, Yuzhang Xie, Joyce C. Ho, Carl Yang

Comments 11 pages, 5 figures, to be published in Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks

Wenying Duan, Tianxiang Fang, Hong Rao, Xiaoxi He

Comments Conference paper, accepted by KDD' 24

Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation

Porter Jenkins, Michael Selander, J. Stockton Jenkins, Andrew Merrill, Kyle Armstrong

Comments Accepted to KDD 2024

How Powerful is Graph Filtering for Recommendation

Shaowen Peng, Xin Liu, Kazunari Sugiyama, Tsunenori Mine

Comments Accepted to KDD'24

Predicting Cascading Failures with a Hyperparametric Diffusion Model

Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan

Comments KDD 2024

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time

Haiyuan Zhao, Guohao Cai, Jieming Zhu, Zhenhua Dong, Jun Xu, Ji-Rong Wen

Comments Accepted by KDD 2024

Learning Metrics that Maximise Power for Accelerated A/B-Tests

Olivier Jeunen, Aleksei Ustimenko

Comments To appear in the Applied Data Science track at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24)

An Efficient Subgraph GNN with Provable Substructure Counting Power

Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang

Comments accepted in KDD 2024

A Self-boosted Framework for Calibrated Ranking

Shunyu Zhang, Hu Liu, Wentian Bao, Enyun Yu, Yang Song

Comments KDD 2024

Multivariate Log-based Anomaly Detection for Distributed Database

Lingzhe Zhang, Tong Jia, Mengxi Jia, Ying Li, Yong Yang, Zhonghai Wu

Comments Accepted by KDD'24

DPSW-Sketch: A Differentially Private Sketch Framework for Frequency Estimation over Sliding Windows (Technical Report)

Yiping Wang, Yanhao Wang, Cen Chen

Comments Accepted for publication at KDD 2024

CAFO: Feature-Centric Explanation on Time Series Classification

Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang, Junghye Lee, Seulki Lee

Comments Accepted to KDD 2024 Research Track

Graph Condensation for Open-World Graph Learning

Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin

Comments Accepted by KDD 2024

Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing

Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma

Comments Accepted by KDD 2024

Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs

Junjie Wang, Dan Yang, Binbin Hu, Yue Shen, Wen Zhang, Jinjie Gu

Comments Accepted by KDD 2024

On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-$n$ Recommendation

Olivier Jeunen, Ivan Potapov, Aleksei Ustimenko

Comments To appear in the research track at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24)