KDD

AI Safety in Practice: Enhancing Adversarial Robustness in Multimodal Image Captioning

Maisha Binte Rashid, Pablo Rivas

Comments Accepted into KDD 2024 workshop on Ethical AI

Medfluencer: A Network Representation of Medical Influencers' Identities and Discourse on Social Media

Zhijin Guo, Edwin Simpson, Roberta Bernardi

Comments ACM SIGKDD 2024 Workshop epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery

Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept

Alexandre Trilla, Ossee Yiboe, Nenad Mijatovic, Jordi Vitrià

Comments 2nd Workshop on Causal Inference and Machine Learning in Practice at the KDD 2024 Conference. arXiv admin note: text overlap with arXiv:2407.11056

NudgeRank: Digital Algorithmic Nudging for Personalized Health

Jodi Chiam, Aloysius Lim, Ankur Teredesai

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

Learning the Covariance of Treatment Effects Across Many Weak Experiments

Aurélien Bibaut, Winston Chou, Simon Ejdemyr, Nathan Kallus

Comments Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

CoLiDR: Concept Learning using Aggregated Disentangled Representations

Sanchit Sinha, Guangzhi Xiong, Aidong Zhang

Comments KDD 2024

Deep State-Space Generative Model For Correlated Time-to-Event Predictions

Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui

Comments Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning

Bobby Chen, Siyu Chen, Jason Dowlatabadi, Yu Xuan Hong, Vinayak Iyer, Uday Mantripragada, Rishabh Narang, Apoorv Pandey, Zijun Qin, Abrar Sheikh, Hongtao Sun, Jiaqi Sun, Matthew Walker, Kaichen Wei, Chen Xu, Jingnan Yang, Allen T. Zhang, Guoqing Zhang

Comments To be published in the 2nd Workshop on Causal Inference and Machine Learning in Practice, KDD 2024, August 25 to 29, 2024, Barcelona, Spain, 10 pages

The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset

Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen

Comments KDD MLF Workshop 2024. Dataset can be accessed at http://elliptic.co/elliptic2. Code can be accessed at https://github.com/MITIBMxGraph/Elliptic2

POSIT: Promotion of Semantic Item Tail via Adversarial Learning

Qiuling Xu, Pannaga Shivaswamy, Xiangyu Zhang

Comments EAI-KDD'2024. Code at https://github.com/qiulingxu/POSIT

Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data

Hanyang Yuan, Jiarong Xu, Cong Wang, Ziqi Yang, Chunping Wang, Keting Yin, Yang Yang

Comments In KDD'24; with full appendix

ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems

Hong Qian, Shuo Liu, Mingjia Li, Bingdong Li, Zhi Liu, Aimin Zhou

Journal ref KDD 2024

A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide

Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin

Comments To appear in KDD 2024 (survey paper). The typo in Equation (5) has been fixed

SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning

Jongha Lee, Sunwoo Kim, Kijung Shin

Comments 12 pages, 4 figures, To Appear in KDD 2024

ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

Tong Nie, Guoyang Qin, Wei Ma, Yuewen Mei, Jian Sun

Comments Accepted by KDD'24 (Research Track)

Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation

Xinyu Lin, Wenjie Wang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua

Comments Accepted by KDD 2024

SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing

Changchang Yin, Pin-Yu Chen, Bingsheng Yao, Dakuo Wang, Jeffrey Caterino, Ping Zhang

Comments To be published in KDD 2024

scGHSOM: Hierarchical clustering and visualization of single-cell and CRISPR data using growing hierarchical SOM

Shang-Jung Wen, Jia-Ming Chang, Fang Yu

Comments Abstract presentation at BIOKDD@ACM KDD 2024

STATE: A Robust ATE Estimator of Heavy-Tailed Metrics for Variance Reduction in Online Controlled Experiments

Hao Zhou, Kun Sun, Shaoming Li, Yangfeng Fan, Guibin Jiang, Jiaqi Zheng, Tao Li

Comments Accepted by KDD 2024

Graph Bottlenecked Social Recommendation

Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang

Comments Accepted by KDD 2024

Pre-Training and Prompting for Few-Shot Node Classification on Text-Attributed Graphs

Huanjing Zhao, Beining Yang, Yukuo Cen, Junyu Ren, Chenhui Zhang, Yuxiao Dong, Evgeny Kharlamov, Shu Zhao, Jie Tang

Comments Accepted to KDD'24

Strategic Coupon Allocation for Increasing Providers' Sales Experiences in Two-sided Marketplaces

Koya Ohashi, Sho Sekine, Deddy Jobson, Jie Yang, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano

Comments 8 pages, 10 figures, KDD 2024 Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth

Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning

Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li

Comments KDD 2024

Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model

Yuxing Tian, Yiyan Qi, Aiwen Jiang, Qi Huang, Jian Guo

Comments Accepted by KDD 2024

Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion

Qinggang Zhang, Keyu Duan, Junnan Dong, Pai Zheng, Xiao Huang

Comments 30th SIGKDD Conference on Knowledge Discovery and Data Mining

PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer

Jiahong Ma, Mingguo He, Zhewei Wei

Comments ACM SIGKDD 2024

A Comparative Study of Deep Reinforcement Learning Models: DQN vs PPO vs A2C

Neil De La Fuente, Daniel A. Vidal Guerra

Comments 8 pages, Accepted at KDD 2024

Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization

Hao Zhou, Rongxiao Huang, Shaoming Li, Guibin Jiang, Jiaqi Zheng, Bing Cheng, Wei Lin

Comments Accepted by KDD 2024

Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection

Chunjing Xiao, Shikang Pang, Wenxin Tai, Yanlong Huang, Goce Trajcevski, Fan Zhou

Comments Accepted by KDD 2024

Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly

Comments Survey Article for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2024) Tutorial

Journal ref Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)