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2024

Generalizing Graph Neural Networks on Out-of-Distribution GraphsShaohua Fan, Xiao Wang 0017, Chuan Shi, Peng Cui 0001, Bai Wang 0001. pami, 46(1):322-337, January 2024. [doi]

2023

Covariate-Shift Generalization via Random Sample WeightingYue He 0001, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui 0001. AAAI 2023: 11828-11836 [doi]

Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and ApplicationsJianxin Li 0001, Lifang He 0001, Hao Peng, Peng Cui 0001, Charu C. Aggarwal, Philip S. Yu. tkde, 35(12):11982-11983, December 2023. [doi]

Factual Observation Based Heterogeneity Learning for Counterfactual PredictionHao Zou 0001, Haotian Wang 0001, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui 0001. clear2 2023: 350-370 [doi]

Adversarial Attack Framework on Graph Embedding Models With Limited KnowledgeHeng Chang, Yu Rong, Tingyang Xu, Wenbing Huang 0001, Honglei Zhang, Peng Cui 0001, Xin Wang 0019, Wenwu Zhu 0001, JunZhou Huang. tkde, 35(5):4499-4513, May 2023. [doi]

Group-based social diffusion in recommendationXumin Chen, Ruobing Xie, Zhijie Qiu, Peng Cui 0001, Ziwei Zhang, Shukai Liu, Shiqiang Yang, Bo Zhang 0056, Leyu Lin. www, 26(4):1775-1792, July 2023. [doi]

Stable Prediction With Leveraging Seed VariableKun Kuang, Haotian Wang, Yue Liu, Ruoxuan Xiong, Runze Wu, Weiming Lu 0001, Yueting Zhuang, Fei Wu 0001, Peng Cui 0001, Bo Li 0064. tkde, 35(6):6392-6404, June 2023. [doi]

Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and DecisionThuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui 0001, Kun Kuang, Jian Pei, Fei Wang 0001, Mattia Prosperi. kddcd 2023: 1-2 [doi]

Propensity Matters: Measuring and Enhancing Balancing for RecommendationHaoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu 0012, Peng Cui 0001. icml 2023: 20182-20194 [doi]

Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for RecommendationHaoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui 0001. kdd 2023: 1235-1247 [doi]

Measure the Predictive HeterogeneityJiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li 0064, Peng Cui 0001. iclr 2023: [doi]

Distributionally Robust Learning With Stable Adversarial TrainingJiashuo Liu, Zheyan Shen, Peng Cui 0001, Linjun Zhou, Kun Kuang, Bo Li 0064. tkde, 35(11):11288-11300, November 2023. [doi]

On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular DatasetsJiashuo Liu, Tianyu Wang, Peng Cui 0001, Hongseok Namkoong. nips 2023: [doi]

A Scalable Social Recommendation Framework with Decoupled Graph Neural NetworkKe Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang 0012, Peng Cui 0001, Xiaolong Li 0005, Jun Zhou 0011. dasfaa 2023: 519-531 [doi]

Causal Disentanglement for Semantic-Aware Intent Learning in RecommendationXiangmeng Wang, Qian Li 0003, Dianer Yu, Peng Cui 0001, Zhichao Wang, Guandong Xu. tkde, 35(10):9836-9849, October 2023. [doi]

A Data-Driven Decision Support Framework for Player Churn Analysis in Online GamesYu Xiong, Runze Wu, Shiwei Zhao, Jianrong Tao, Xudong Shen, Tangjie Lyu, Changjie Fan, Peng Cui 0001. kdd 2023: 5303-5314 [doi]

Competing for Shareable Arms in Multi-Player Multi-Armed BanditsRenzhe Xu, Haotian Wang 0001, Xingxuan Zhang, Bo Li, Peng Cui 0001. icml 2023: 38674-38706 [doi]

Flatness-Aware Minimization for Domain GeneralizationXingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui 0001. iccv 2023: 5166-5179 [doi]

NICO++: Towards Better Benchmarking for Domain GeneralizationXingxuan Zhang, Yue He 0001, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui 0001. cvpr 2023: 16036-16047 [doi]

Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves GeneralizationXingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou 0001, Peng Cui 0001. cvpr 2023: 20247-20257 [doi]

Eigen-GNN: A Graph Structure Preserving Plug-in for GNNsZiwei Zhang, Peng Cui 0001, Jian Pei, Xin Wang 0019, Wenwu Zhu 0001. tkde, 35(3):2544-2555, March 2023. [doi]

Permutation-Equivariant and Proximity-Aware Graph Neural Networks With Stochastic Message PassingZiwei Zhang, Chenhao Niu, Peng Cui 0001, Jian Pei, Bo Zhang 0056, Wenwu Zhu 0001. tkde, 35(6):6182-6193, June 2023. [doi]

Differentiated matching for individual and average treatment effect estimationZhao Ziyu, Kun Kuang, Bo Li 0064, Peng Cui 0001, Runze Wu, Jun Xiao 0001, Fei Wu 0001. datamine, 37(1):205-227, 2023. [doi]

2022

Stable learning establishes some common ground between causal inference and machine learningPeng Cui 0001, Susan Athey. natmi, 4(2):110-115, 2022. [doi]

CausPref: Causal Preference Learning for Out-of-Distribution RecommendationYue He 0001, Zimu Wang, Peng Cui 0001, Hao Zou 0001, Yafeng Zhang, Qiang Cui, Yong Jiang 0001. WWW 2022: 410-421 [doi]

Bilateral Filtering Graph Convolutional Network for Multi-relational Social Recommendation in the Power-law NetworksMinghao Zhao 0002, Qilin Deng, Kai Wang, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui 0001. tois, 40(2), 2022. [doi]

Dynamic Heterogeneous Information Network Embedding With Meta-Path Based ProximityXiao Wang 0017, Yuanfu Lu, Chuan Shi, Ruijia Wang, Peng Cui 0001, Shuai Mou. tkde, 34(3):1117-1132, 2022. [doi]

Data-Driven Variable Decomposition for Treatment Effect EstimationKun Kuang, Peng Cui 0001, Hao Zou 0001, Bo Li 0064, Jianrong Tao, Fei Wu 0001, Shiqiang Yang. tkde, 34(5):2120-2134, 2022. [doi]

Intention-Aware Sequential Recommendation With Structured Intent TransitionHaoyang Li, Xin Wang 0019, Ziwei Zhang, Jianxin Ma, Peng Cui 0001, Wenwu Zhu 0001. tkde, 34(11):5403-5414, 2022. [doi]

ZIN: When and How to Learn Invariance Without Environment Partition?Yong Lin, Shengyu Zhu 0001, Lu Tan, Peng Cui 0001. nips 2022: [doi]

Distributionally Robust Optimization with Data GeometryJiashuo Liu, Jiayun Wu, Bo Li 0064, Peng Cui 0001. nips 2022: [doi]

Uncovering the Heterogeneous Effects of Preference Diversity on User Activeness: A Dynamic Mixture ModelYunfei Lu, Peng Cui 0001, Linyun Yu, Lei Li 0005, Wenwu Zhu 0001. kdd 2022: 3458-3467 [doi]

Distilling Causal Metaknowledge from Knowledge GraphsYuan Meng, Yancheng Dong, Shixuan Liu, Chaohao Yuan, Yue He 0001, Jian Pei, Peng Cui 0001. DEBU, 45(4):102-121, 2022. [doi]

Invariant Preference Learning for General Debiasing in RecommendationZimu Wang, Yue He 0001, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui 0001. kdd 2022: 1969-1978 [doi]

Improving Accuracy and Diversity in Matching of Recommendation With Diversified Preference NetworkRuobing Xie, Qi Liu, Shukai Liu, Ziwei Zhang, Peng Cui 0001, Bo Zhang 0056, Leyu Lin. tbd, 8(4):955-967, 2022. [doi]

Regulatory Instruments for Fair Personalized PricingRenzhe Xu, Xingxuan Zhang, Peng Cui 0001, Bo Li 0064, Zheyan Shen, Jiazheng Xu. WWW 2022: 4-15 [doi]

Product Ranking for Revenue Maximization with Multiple PurchasesRenzhe Xu, Xingxuan Zhang, Bo Li 0064, Yafeng Zhang, Xiaolong Chen, Peng Cui 0001. nips 2022: [doi]

A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift GeneralizationRenzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui 0001. icml 2022: 24803-24829 [doi]

Towards Unsupervised Domain GeneralizationXingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui 0001, Zheyan Shen, Haoxin Liu. cvpr 2022: 4900-4910 [doi]

NICO Challenge: Out-of-Distribution Generalization for Image Recognition ChallengesXingxuan Zhang, Yue He 0001, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui 0001. eccv 2023: 433-450 [doi]

Deep Learning on Graphs: A SurveyZiwei Zhang, Peng Cui 0001, Wenwu Zhu 0001. tkde, 34(1):249-270, 2022. [doi]

Adversarial Eigen Attack on BlackBox ModelsLinjun Zhou, Peng Cui 0001, Xingxuan Zhang, Yinan Jiang, Shiqiang Yang. cvpr 2022: 15233-15241 [doi]

2021

On the Equivalence of Decoupled Graph Convolution Network and Label PropagationHande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui 0001. WWW 2021: 3651-3662 [doi]

Towards Non-I.I.D. image classification: A dataset and baselinesYue He, Zheyan Shen, Peng Cui 0001. PR, 110:107383, 2021. [doi]

DARING: Differentiable Causal Discovery with Residual IndependenceYue He, Peng Cui 0001, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang. kdd 2021: 596-605 [doi]

Continuous treatment effect estimation via generative adversarial de-confoundingKun Kuang, Yunzhe Li, Bo Li 0064, Peng Cui 0001, Hongxia Yang, Jianrong Tao, Fei Wu 0001. datamine, 35(6):2467-2497, 2021. [doi]

Stable Adversarial Learning under Distributional ShiftsJiashuo Liu, Zheyan Shen, Peng Cui 0001, Linjun Zhou, Kun Kuang, Bo Li 0064, Yishi Lin. AAAI 2021: 8662-8670 [doi]

Signed Graph Neural Network with Latent GroupsHaoxin Liu, Ziwei Zhang, Peng Cui 0001, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu 0001. kdd 2021: 1066-1075 [doi]

Kernelized Heterogeneous Risk MinimizationJiashuo Liu, Zheyuan Hu, Peng Cui 0001, Bo Li 0064, Zheyan Shen. nips 2021: 21720-21731 [doi]

Heterogeneous Risk MinimizationJiashuo Liu, Zheyuan Hu, Peng Cui 0001, Bo Li 0064, Zheyan Shen. icml 2021: 6804-6814 [doi]

Collaborative Learning for Extremely Low Bit Asymmetric HashingYadan Luo, Zi Huang, Yang Li, Fumin Shen, Yang Yang 0002, Peng Cui 0001. tkde, 33(12):3675-3685, 2021. [doi]

Deep Stable Learning for Out-of-Distribution GeneralizationXingxuan Zhang, Peng Cui 0001, Renzhe Xu, Linjun Zhou, Yue He 0001, Zheyan Shen. cvpr 2021: 5372-5382 [doi]

Interpreting and Unifying Graph Neural Networks with An Optimization FrameworkMeiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui 0001. WWW 2021: 1215-1226 [doi]

2020

AM-GCN: Adaptive Multi-channel Graph Convolutional NetworksXiao Wang 0017, Meiqi Zhu, Deyu Bo, Peng Cui 0001, Chuan Shi, Jian Pei. kdd 2020: 1243-1253 [doi]

Structural Deep Clustering NetworkDeyu Bo, Xiao Wang 0017, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui 0001. WWW 2020: 1400-1410 [doi]

Stable Prediction with Model Misspecification and Agnostic Distribution ShiftKun Kuang, Ruoxuan Xiong, Peng Cui 0001, Susan Athey, Bo Li 0064. AAAI 2020: 4485-4492 [doi]

Treatment Effect Estimation via Differentiated Confounder Balancing and RegressionKun Kuang, Peng Cui 0001, Bo Li 0064, Meng Jiang 0001, Yashen Wang, Fei Wu, Shiqiang Yang. tkdd, 14(1), 2020. [doi]

Preface: The 2020 ACM SIGKDD Workshop on Causal DiscoveryThuc Duy Le, Lin Liu 0003, Kun Zhang 0001, Emre Kiciman, Peng Cui 0001, Aapo Hyvärinen. kdd 2020: 1-3 [doi]

Continuous Treatment Effect Estimation via Generative Adversarial De-confoundingYunzhe Li, Kun Kuang, Bo Li 0064, Peng Cui 0001, Jianrong Tao, Hongxia Yang, Fei Wu 0001. kdd 2020: 4-22 [doi]

Exploring the collective human behavior in cascading systems: a comprehensive frameworkYunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui 0001, Chaoming Song, Wenwu Zhu 0001. kais, 62(12):4599-4623, 2020. [doi]

Stable Learning via Sample ReweightingZheyan Shen, Peng Cui 0001, Tong Zhang, Kun Kuang. AAAI 2020: 5692-5699 [doi]

Stable Learning via Differentiated Variable DecorrelationZheyan Shen, Peng Cui 0001, Jiashuo Liu, Tong Zhang, Bo Li 0064, Zhitang Chen. kdd 2020: 2185-2193 [doi]

Network embedding in biomedical data scienceChang Su, Jie Tong, Yongjun Zhu, Peng Cui 0001, Fei Wang 0001. bib, 21(1):182-197, 2020. [doi]

Algorithmic Decision Making with Conditional FairnessRenzhe Xu, Peng Cui 0001, Kun Kuang, Bo Li 0064, Linjun Zhou, Zheyan Shen, Wei Cui. kdd 2020: 2125-2135 [doi]

Learning to Select Base Classes for Few-Shot ClassificationLinjun Zhou, Peng Cui 0001, Xu Jia, Shiqiang Yang, Qi Tian 0001. cvpr 2020: 4623-4632 [doi]

Counterfactual Prediction for Bundle TreatmentHao Zou, Peng Cui 0001, Bo Li 0064, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He. nips 2020: [doi]

2019

A Survey on Network EmbeddingPeng Cui 0001, Xiao Wang, Jian Pei, Wenwu Zhu 0001. tkde, 31(5):833-852, 2019. [doi]

Learning From Networks: Algorithms, Theory, and ApplicationsXiao Huang, Peng Cui 0001, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang 0001, Hongxia Yang, Wenwu Zhu 0001. kdd 2019: 3221-3222 [doi]

Preface: The 2019 ACM SIGKDD Workshop on Causal DiscoveryThuc Duy Le, Jiuyong Li, Kun Zhang 0001, Emre Kiciman, Peng Cui 0001, Aapo Hyvärinen. kdd 2019: 1-3 [doi]

Causation-Driven Visualizations for Insurance RecommendationZhixiu Liu, Chengxi Zang, Kun Kuang, Hao Zou, Hu Zheng, Peng Cui 0001. icmcs 2019: 471-476 [doi]

Uncovering the Co-driven Mechanism of Social and Content Links in User Churn PhenomenaYunfei Lu, Linyun Yu, Peng Cui 0001, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu 0001. kdd 2019: 3093-3101 [doi]

Learning Disentangled Representations for RecommendationJianxin Ma, Chang Zhou, Peng Cui 0001, Hongxia Yang, Wenwu Zhu 0001. nips 2019: 5712-5723 [doi]

Disentangled Graph Convolutional NetworksJianxin Ma, Peng Cui 0001, Kun Kuang, Xin Wang, Wenwu Zhu 0001. icml 2019: 4212-4221 [doi]

AutoNE: Hyperparameter Optimization for Massive Network EmbeddingKe Tu, Jianxin Ma, Peng Cui 0001, Jian Pei, Wenwu Zhu 0001. kdd 2019: 216-225 [doi]

A Semi-Supervised Graph Attentive Network for Financial Fraud DetectionDaixin Wang, Yuan Qi, Jianbin Lin, Peng Cui 0001, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang. icdm 2019: 598-607 [doi]

Disparity-preserved Deep Cross-platform Association for Cross-platform Video RecommendationShengze Yu, Xin Wang, Wenwu Zhu 0001, Peng Cui 0001, Jingdong Wang. IJCAI 2019: 4635-4641 [doi]

Video Summarization by Learning Deep Side Semantic EmbeddingYitian Yuan, Tao Mei, Peng Cui 0001, Wenwu Zhu 0001. tcsv, 29(1):226-237, 2019. [doi]

Uncovering Pattern Formation of Information FlowChengxi Zang, Peng Cui 0001, Chaoming Song, Wenwu Zhu 0001, Fei Wang. kdd 2019: 1691-1699 [doi]

Robust Graph Convolutional Networks Against Adversarial AttacksDingyuan Zhu, Ziwei Zhang, Peng Cui 0001, Wenwu Zhu 0001. kdd 2019: 1399-1407 [doi]

Focused Context Balancing for Robust Offline Policy EvaluationHao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui 0001. kdd 2019: 696-704 [doi]

2018

Scalable Optimization for Embedding Highly-Dynamic and Recency-Sensitive DataXumin Chen, Peng Cui 0001, Lingling Yi, Shiqiang Yang. kdd 2018: 130-138 [doi]

Effective Promotional Strategies Selection in Social Media: A Data-Driven ApproachKun Kuang, Meng Jiang 0001, Peng Cui 0001, Hengliang Luo, Shiqiang Yang. tbd, 4(4):487-501, 2018. [doi]

Stable Prediction across Unknown EnvironmentsKun Kuang, Peng Cui 0001, Susan Athey, Ruoxuan Xiong, Bo Li. kdd 2018: 1617-1626 [doi]

Collective Human Behavior in Cascading System: Discovery, Modeling and ApplicationsYunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui 0001, Chaoming Song, Wenwu Zhu 0001. icdm 2018: 297-306 [doi]

Hierarchical Taxonomy Aware Network EmbeddingJianxin Ma, Peng Cui 0001, Xiao Wang, Wenwu Zhu 0001. kdd 2018: 1920-1929 [doi]

Causally Regularized Learning with Agnostic Data Selection BiasZheyan Shen, Peng Cui 0001, Kun Kuang, Bo Li, Peixuan Chen. mm 2018: 411-419 [doi]

Deep Recursive Network Embedding with Regular EquivalenceKe Tu, Peng Cui 0001, Xiao Wang, Philip S. Yu, Wenwu Zhu 0001. kdd 2018: 2357-2366 [doi]

On Power Law Growth of Social NetworksChengxi Zang, Peng Cui 0001, Christos Faloutsos, Wenwu Zhu 0001. tkde, 30(9):1727-1740, 2018. [doi]

Learning and Interpreting Complex Distributions in Empirical DataChengxi Zang, Peng Cui 0001, Wenwu Zhu 0001. kdd 2018: 2682-2691 [doi]

Arbitrary-Order Proximity Preserved Network EmbeddingZiwei Zhang, Peng Cui 0001, Xiao Wang, Jian Pei, Xuanrong Yao, Wenwu Zhu 0001. kdd 2018: 2778-2786 [doi]

Deep Variational Network Embedding in Wasserstein SpaceDingyuan Zhu, Peng Cui 0001, Daixin Wang, Wenwu Zhu 0001. kdd 2018: 2827-2836 [doi]

High-Order Proximity Preserved Embedding for Dynamic NetworksDingyuan Zhu, Peng Cui 0001, Ziwei Zhang, Jian Pei, Wenwu Zhu 0001. tkde, 30(11):2134-2144, 2018. [doi]

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