KDD

Counterfactual Phenotyping with Censored Time-to-Events

Chirag Nagpal, Mononito Goswami, Keith Dufendach, Artur Dubrawski

Comments KDD 2022 Applied Data Science Paper. Note this version includes a correction of the published version in the definition of Restricted Mean Survival Time

Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing

Lihan Wang, Bowen Qin, Binyuan Hui, Bowen Li, Min Yang, Bailin Wang, Binhua Li, Fei Huang, Luo Si, Yongbin Li

Comments Accepted at KDD 2022

Interpretable Personalized Experimentation

Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel Jiang, Eytan Bakshy

Comments Camera-ready version for KDD 2022. Previously titled "Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies". A short version was presented at MIT CODE 2021

Evolution of Popularity Bias: Empirical Study and Debiasing

Ziwei Zhu, Yun He, Xing Zhao, James Caverlee

Comments Accepted at KDD 2022 Workshop on Data Science and Artificial Intelligence for Responsible Recommendations (DS4RRS)

Scrutinizing Shipment Records To Thwart Illegal Timber Trade

Debanjan Datta, Sathappan Muthiah, John Simeone, Amelia Meadows, Naren Ramakrishnan

Comments Accepted in Proceedings of 6th Outlier Detection and Description Workshop, ACM SigKDD 2021 https://oddworkshop.github.io/assets/papers/7.pdf. arXiv admin note: substantial text overlap with arXiv:2104.01156

Some Practice for Improving the Search Results of E-commerce

Fanyou Wu, Yang Liu, Rado Gazo, Benes Bedrich, Xiaobo Qu

Comments Submitted to Amazon KDD Cup 2022 workshop

FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou

Comments Accpeted by KDD'2022; We have released FederatedScope for users on https://github.com/alibaba/FederatedScope

Personalized Promotion Decision Making Based on Direct and Enduring Effect Predictions

Jie Yang, Yilin Li, Deddy Jobson

Journal ref 1st Workshop on End-End Customer Journey Optimization at KDD 2022

Self-Supervised Hypergraph Transformer for Recommender Systems

Lianghao Xia, Chao Huang, Chuxu Zhang

Comments This paper has been published as a full paper at the KDD research track 2022

On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification

Erik Schultheis, Marek Wydmuch, Rohit Babbar, Krzysztof Dembczyński

Comments This is the author's version of the work accepted at KDD '22

How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications

Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra

Comments KDD 2022 camera ready version + full appendix; 20 pages, 2 figures

Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach

Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang

Comments To appear in SIGKDD 2022 as Research Track paper

Democratizing Ethical Assessment of Natural Language Generation Models

Amin Rasekh, Ian Eisenberg

Comments 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), August 14-18, 2022, Washington, DC

Knowledge-enhanced Black-box Attacks for Recommendations

Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, Yihua Huang

Comments Accepted in the KDD'22

CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution

Di Yao, Chang Gong, Lei Zhang, Sheng Chen, Jingping Bi

Comments 11 pages, 5 figures This paper has been accepted in KDD 2022

HICF: Hyperbolic Informative Collaborative Filtering

Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King

Comments Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22)

Unified 2D and 3D Pre-Training of Molecular Representations

Jinhua Zhu, Yingce Xia, Lijun Wu, Shufang Xie, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

Comments KDD-2022

Greykite: Deploying Flexible Forecasting at Scale at LinkedIn

Reza Hosseini, Albert Chen, Kaixu Yang, Sayan Patra, Yi Su, Saad Eddin Al Orjany, Sishi Tang, Parvez Ahammad

Comments In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), August 14-18, 2022, Washington, DC, USA. ACM, New York, NY, USA, 11 pages

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks

Xiong Peng, Feng Liu, Jingfen Zhang, Long Lan, Junjie Ye, Tongliang Liu, Bo Han

Comments Accepted to KDD 2022 (Research Track)

Journal ref Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)

ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learning

Haozhe Wang, Chao Du, Panyan Fang, Shuo Yuan, Xuming He, Liang Wang, Bo Zheng

Comments Accepted by SIGKDD 2022

OASYS: Domain-Agnostic Automated System for Constructing Knowledge Base from Unstructured Text

Minsang Kim, Sang-hyun Je, Eunjoo Park

Comments ACM SIGKDD Workshop on Mining and Learning with Graphs 2022, Accepted

Joint Application of the Target Trial Causal Framework and Machine Learning Modeling to Optimize Antibiotic Therapy: Use Case on Acute Bacterial Skin and Skin Structure Infections due to Methicillin-resistant Staphylococcus aureus

Inyoung Jun, Simone Marini, Christina A. Boucher, J. Glenn Morris, Jiang Bian, Mattia Prosperi

Comments This is the Proceedings of the KDD workshop on Applied Data Science for Healthcare (DSHealth 2022), which was held on Washington D.C, August 14 2022

GrabQC: Graph based Query Contextualization for automated ICD coding

Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran

Comments 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2021)

Subgraph Frequency Distribution Estimation using Graph Neural Networks

Zhongren Chen, Xinyue Xu, Shengyi Jiang, Hao Wang, Lu Mi

Comments accepted by KDD 2022 Workshop on Deep Learning on Graphs

In Defense of Core-set: A Density-aware Core-set Selection for Active Learning

Yeachan Kim, Bonggun Shin

Comments Proceedings of the ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2022 (KDD'22)

Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions

José Pombal, André F. Cruz, João Bravo, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro

Comments KDD'22 Workshop on Machine Learning in Finance

GraphMAE: Self-Supervised Masked Graph Autoencoders

Zhenyu Hou, Xiao Liu, Yukuo Cen, Yuxiao Dong, Hongxia Yang, Chunjie Wang, Jie Tang

Comments 11 pages; Accepted to KDD'22

Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes

Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana

Comments DSHealth at SIGKDD 2022, 5 pages, 3 figures

Multi-task Envisioning Transformer-based Autoencoder for Corporate Credit Rating Migration Early Prediction

Han Yue, Steve Xia, Hongfu Liu

Comments SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition

Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook

Comments 8th SIGKDD International Workshop on Mining and Learning from Time Series, 2022