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Peng Cui 0001
Person information

- affiliation (PhD 2010): Tsinghua University, Department of Computer Science and Technology, Beijing, China
Other persons with the same name
- Peng Cui — disambiguation page
- Peng Cui 0002
— Northwestern Polytechnical University, School of Marine Science and Technology, Xi'an, China
- Peng Cui 0003
— Shanghai Jiao Tong University, School of Life Science and Biotechnology / Shanghai Center for Bioinformation Technology, China
- Peng Cui 0004
— Chinese Academy of Agricultural Sciences, Agricultural Genomics Institute at Shenzhen, China (and 3 more)
- Peng Cui 0005 — Shandong University, School of Control Science and Engineering, Jinan, China
- Peng Cui 0006 — Harbin Institute of Technology, School of Computer Science and Technology, China
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2020 – today
- 2023
- [j54]Zhao Ziyu
, Kun Kuang, Bo Li, Peng Cui, Runze Wu, Jun Xiao, Fei Wu:
Differentiated matching for individual and average treatment effect estimation. Data Min. Knowl. Discov. 37(1): 205-227 (2023) - [j53]Ziwei Zhang
, Peng Cui
, Jian Pei
, Xin Wang
, Wenwu Zhu
:
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs. IEEE Trans. Knowl. Data Eng. 35(3): 2544-2555 (2023) - [j52]Heng Chang
, Yu Rong
, Tingyang Xu, Wenbing Huang
, Honglei Zhang, Peng Cui
, Xin Wang
, Wenwu Zhu
, Junzhou Huang
:
Adversarial Attack Framework on Graph Embedding Models With Limited Knowledge. IEEE Trans. Knowl. Data Eng. 35(5): 4499-4513 (2023) - [j51]Ziwei Zhang
, Chenhao Niu, Peng Cui
, Jian Pei
, Bo Zhang
, Wenwu Zhu
:
Permutation-Equivariant and Proximity-Aware Graph Neural Networks With Stochastic Message Passing. IEEE Trans. Knowl. Data Eng. 35(6): 6182-6193 (2023) - [j50]Kun Kuang
, Haotian Wang, Yue Liu, Ruoxuan Xiong, Runze Wu
, Weiming Lu
, Yueting Zhuang, Fei Wu
, Peng Cui
, Bo Li
:
Stable Prediction With Leveraging Seed Variable. IEEE Trans. Knowl. Data Eng. 35(6): 6392-6404 (2023) - [c138]Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Peng Cui, Xiaolong Li, Jun Zhou:
A Scalable Social Recommendation Framework with Decoupled Graph Neural Network. DASFAA (4) 2023: 519-531 - [c137]Jie Peng
, Hao Zou
, Jiashuo Liu
, Shaoming Li
, Yibao Jiang
, Jian Pei
, Peng Cui
:
Offline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping. WWW 2023: 1220-1230 - [i61]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. CoRR abs/2301.09819 (2023) - [i60]Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui:
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CoRR abs/2303.03108 (2023) - [i59]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Predictive Heterogeneity: Measures and Applications. CoRR abs/2304.00305 (2023) - [i58]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CoRR abs/2305.15253 (2023) - [i57]Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui:
Exploring and Exploiting Data Heterogeneity in Recommendation. CoRR abs/2305.15431 (2023) - [i56]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. CoRR abs/2305.19158 (2023) - 2022
- [j49]Yuan Meng, Yancheng Dong, Shixuan Liu, Chaohao Yuan, Yue He, Jian Pei, Peng Cui:
Distilling Causal Metaknowledge from Knowledge Graphs. IEEE Data Eng. Bull. 45(4): 102-121 (2022) - [j48]Peng Cui, Susan Athey
:
Stable learning establishes some common ground between causal inference and machine learning. Nat. Mach. Intell. 4(2): 110-115 (2022) - [j47]Ruobing Xie
, Qi Liu
, Shukai Liu
, Ziwei Zhang
, Peng Cui
, Bo Zhang
, Leyu Lin
:
Improving Accuracy and Diversity in Matching of Recommendation With Diversified Preference Network. IEEE Trans. Big Data 8(4): 955-967 (2022) - [j46]Ziwei Zhang
, Peng Cui
, Wenwu Zhu
:
Deep Learning on Graphs: A Survey. IEEE Trans. Knowl. Data Eng. 34(1): 249-270 (2022) - [j45]Xiao Wang
, Yuanfu Lu
, Chuan Shi
, Ruijia Wang
, Peng Cui
, Shuai Mou:
Dynamic Heterogeneous Information Network Embedding With Meta-Path Based Proximity. IEEE Trans. Knowl. Data Eng. 34(3): 1117-1132 (2022) - [j44]Kun Kuang
, Peng Cui
, Hao Zou, Bo Li
, Jianrong Tao
, Fei Wu
, Shiqiang Yang:
Data-Driven Variable Decomposition for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. 34(5): 2120-2134 (2022) - [j43]Haoyang Li
, Xin Wang
, Ziwei Zhang
, Jianxin Ma, Peng Cui
, Wenwu Zhu
:
Intention-Aware Sequential Recommendation With Structured Intent Transition. IEEE Trans. Knowl. Data Eng. 34(11): 5403-5414 (2022) - [j42]Minghao Zhao
, Qilin Deng, Kai Wang, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui:
Bilateral Filtering Graph Convolutional Network for Multi-relational Social Recommendation in the Power-law Networks. ACM Trans. Inf. Syst. 40(2): 31:1-31:24 (2022) - [c136]Xingxuan Zhang, Linjun Zhou, Renzhe Xu
, Peng Cui, Zheyan Shen, Haoxin Liu:
Towards Unsupervised Domain Generalization. CVPR 2022: 4900-4910 - [c135]Linjun Zhou, Peng Cui, Xingxuan Zhang, Yinan Jiang, Shiqiang Yang:
Adversarial Eigen Attack on BlackBox Models. CVPR 2022: 15233-15241 - [c134]Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui:
NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges. ECCV Workshops (6) 2022: 433-450 - [c133]Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui:
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML 2022: 24803-24829 - [c132]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. ICML 2022: 27203-27221 - [c131]Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding, Peng Cui:
Counterfactual Prediction for Outcome-Oriented Treatments. ICML 2022: 27693-27706 - [c130]Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui:
Invariant Preference Learning for General Debiasing in Recommendation. KDD 2022: 1969-1978 - [c129]Yunfei Lu, Peng Cui, Linyun Yu, Lei Li, Wenwu Zhu:
Uncovering the Heterogeneous Effects of Preference Diversity on User Activeness: A Dynamic Mixture Model. KDD 2022: 3458-3467 - [c128]Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou:
A Graph Learning Based Framework for Billion-Scale Offline User Identification. KDD 2022: 4001-4009 - [c127]Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui:
ZIN: When and How to Learn Invariance Without Environment Partition? NeurIPS 2022 - [c126]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Distributionally Robust Optimization with Data Geometry. NeurIPS 2022 - [c125]Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui:
Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS 2022 - [c124]Renzhe Xu
, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. WWW 2022: 4-15 - [c123]Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang:
CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. WWW 2022: 410-421 - [i55]Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang:
CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. CoRR abs/2202.03984 (2022) - [i54]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. CoRR abs/2202.04245 (2022) - [i53]Yong Lin, Shengyu Zhu, Peng Cui:
ZIN: When and How to Learn Invariance by Environment Inference? CoRR abs/2203.05818 (2022) - [i52]Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li:
Towards Domain Generalization in Object Detection. CoRR abs/2203.14387 (2022) - [i51]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CoRR abs/2204.08040 (2022) - [i50]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou
, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i49]Jiashuo Liu, Jiayun Wu, Jie Peng, Zheyan Shen, Bo Li, Peng Cui:
Distributionally Invariant Learning: Rationalization and Practical Algorithms. CoRR abs/2206.02990 (2022) - [i48]Renzhe Xu
, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui:
Product Ranking for Revenue Maximization with Multiple Purchases. CoRR abs/2210.08268 (2022) - [i47]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. CoRR abs/2212.00992 (2022) - 2021
- [j41]Kun Kuang
, Yunzhe Li, Bo Li, Peng Cui, Hongxia Yang, Jianrong Tao, Fei Wu:
Continuous treatment effect estimation via generative adversarial de-confounding. Data Min. Knowl. Discov. 35(6): 2467-2497 (2021) - [j40]Yue He, Zheyan Shen, Peng Cui:
Towards Non-I.I.D. image classification: A dataset and baselines. Pattern Recognit. 110: 107383 (2021) - [j39]Yadan Luo
, Zi Huang
, Yang Li, Fumin Shen
, Yang Yang
, Peng Cui
:
Collaborative Learning for Extremely Low Bit Asymmetric Hashing. IEEE Trans. Knowl. Data Eng. 33(12): 3675-3685 (2021) - [c122]Kai Wang, Zhene Zou, Qilin Deng, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui:
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation. AAAI 2021: 4427-4435 - [c121]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Stable Adversarial Learning under Distributional Shifts. AAAI 2021: 8662-8670 - [c120]Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu:
Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation. CIKM 2021: 1834-1843 - [c119]Xingxuan Zhang, Peng Cui, Renzhe Xu
, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-of-Distribution Generalization. CVPR 2021: 5372-5382 - [c118]Yijian Qin, Xin Wang, Peng Cui, Wenwu Zhu:
GQNAS: Graph Q Network for Neural Architecture Search. ICDM 2021: 1288-1293 - [c117]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. ICML 2021: 6804-6814 - [c116]Yue He, Peng Cui, Zheyan Shen, Renzhe Xu
, Furui Liu, Yong Jiang:
DARING: Differentiable Causal Discovery with Residual Independence. KDD 2021: 596-605 - [c115]Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu:
Signed Graph Neural Network with Latent Groups. KDD 2021: 1066-1075 - [c114]Qilin Deng, Hao Li, Kai Wang, Zhipeng Hu, Runze Wu, Linxia Gong, Jianrong Tao, Changjie Fan, Peng Cui:
Globally Optimized Matchmaking in Online Games. KDD 2021: 2753-2763 - [c113]Yue He, Yancheng Dong, Peng Cui, Yuhang Jiao, Xiaowei Wang, Ji Liu, Philip S. Yu:
Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors. KDD 2021: 3002-3010 - [c112]Xin Wang, Peng Cui, Wenwu Zhu:
Out-of-distribution Generalization and Its Applications for Multimedia. ACM Multimedia 2021: 5681-5682 - [c111]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. NeurIPS 2021: 21720-21731 - [c110]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. WWW 2021: 1215-1226 - [c109]Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui:
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation. WWW 2021: 3651-3662 - [i46]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. CoRR abs/2101.11859 (2021) - [i45]Ruobing Xie, Qi Liu, Shukai Liu, Ziwei Zhang, Peng Cui, Bo Zhang, Leyu Lin:
Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network. CoRR abs/2102.03787 (2021) - [i44]Kai Wang, Zhene Zou, Qilin Deng, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui:
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation. CoRR abs/2104.02981 (2021) - [i43]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-Of-Distribution Generalization. CoRR abs/2104.07876 (2021) - [i42]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. CoRR abs/2105.03818 (2021) - [i41]Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Xin Wang, Wenwu Zhu, Junzhou Huang:
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge. CoRR abs/2105.12419 (2021) - [i40]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning with Stable Adversarial Training. CoRR abs/2106.15791 (2021) - [i39]Yang Li, Yadan Luo, Zheng Zhang, Shazia W. Sadiq, Peng Cui:
Context-Aware Attention-Based Data Augmentation for POI Recommendation. CoRR abs/2106.15984 (2021) - [i38]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization. CoRR abs/2107.06219 (2021) - [i37]Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui:
Towards Out-Of-Distribution Generalization: A Survey. CoRR abs/2108.13624 (2021) - [i36]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. CoRR abs/2110.12425 (2021) - [i35]Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu:
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation. CoRR abs/2111.02100 (2021) - [i34]Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang:
Why Stable Learning Works? A Theory of Covariate Shift Generalization. CoRR abs/2111.02355 (2021) - [i33]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs. CoRR abs/2111.10657 (2021) - [i32]Ziwei Zhang, Xin Wang, Zeyang Zhang, Peng Cui, Wenwu Zhu:
Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need? CoRR abs/2112.12345 (2021) - 2020
- [j38]Chang Su
, Jie Tong, Yongjun Zhu, Peng Cui, Fei Wang:
Network embedding in biomedical data science. Briefings Bioinform. 21(1): 182-197 (2020) - [j37]Yunfei Lu
, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu:
Exploring the collective human behavior in cascading systems: a comprehensive framework. Knowl. Inf. Syst. 62(12): 4599-4623 (2020) - [j36]Kun Kuang
, Peng Cui, Bo Li, Meng Jiang, Yashen Wang, Fei Wu, Shiqiang Yang:
Treatment Effect Estimation via Differentiated Confounder Balancing and Regression. ACM Trans. Knowl. Discov. Data 14(1): 6:1-6:25 (2020) - [c108]Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, Xiaowei Zhang
:
Rule-Guided Compositional Representation Learning on Knowledge Graphs. AAAI 2020: 2950-2958 - [c107]Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang:
A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models. AAAI 2020: 3389-3396 - [c106]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction with Model Misspecification and Agnostic Distribution Shift. AAAI 2020: 4485-4492 - [c105]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. AAAI 2020: 5692-5699 - [c104]Qi Liu, Ruobing Xie, Lei Chen, Shukai Liu, Ke Tu, Peng Cui, Bo Zhang, Leyu Lin:
Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation. CIKM 2020: 2613-2620 - [c103]Kai Wang, Hao Li, Linxia Gong, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui:
Match Tracing: A Unified Framework for Real-time Win Prediction and Quantifiable Performance Evaluation. CIKM 2020: 2781-2788 - [c102]Linjun Zhou, Peng Cui, Xu Jia, Shiqiang Yang, Qi Tian:
Learning to Select Base Classes for Few-Shot Classification. CVPR 2020: 4623-4632 - [c101]Thuc Duy Le, Lin Liu, Kun Zhang, Emre Kiciman, Peng Cui, Aapo Hyvärinen:
Preface: The 2020 ACM SIGKDD Workshop on Causal Discovery. CD@KDD 2020: 1-3 - [c100]Yunzhe Li, Kun Kuang, Bo Li, Peng Cui, Jianrong Tao, Hongxia Yang, Fei Wu:
Continuous Treatment Effect Estimation via Generative Adversarial De-confounding. CD@KDD 2020: 4-22 - [c99]Jianxin Ma, Chang Zhou, Hongxia Yang, Peng Cui, Xin Wang, Wenwu Zhu:
Disentangled Self-Supervision in Sequential Recommenders. KDD 2020: 483-491 - [c98]Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei
:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. KDD 2020: 1243-1253 - [c97]Renzhe Xu
, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. KDD 2020: 2125-2135 - [c96]Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. KDD 2020: 2185-2193 - [c95]Yue He, Peng Cui, Jianxin Ma, Hao Zou, Xiaowei Wang, Hongxia Yang, Philip S. Yu:
Learning Stable Graphs from Multiple Environments with Selection Bias. KDD 2020: 2194-2202 - [c94]Linxia Gong, Xiaochuan Feng, Dezhi Ye, Hao Li, Runze Wu, Jianrong Tao, Changjie Fan, Peng Cui:
OptMatch: Optimized Matchmaking via Modeling the High-Order Interactions on the Arena. KDD 2020: 2300-2310 - [c93]Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao:
Causal Inference Meets Machine Learning. KDD 2020: 3527-3528 - [c92]Fei Wang, Peng Cui, Jian Pei
, Yangqiu Song, Chengxi Zang:
Recent Advances on Graph Analytics and Its Applications in Healthcare. KDD 2020: 3545-3546 - [c91]Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He:
Counterfactual Prediction for Bundle Treatment. NeurIPS 2020 - [c90]Deyu Bo
, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui:
Structural Deep Clustering Network. WWW 2020: 1400-1410 - [e5]Thuc Duy Le, Lin Liu, Kun Zhang, Emre Kiciman, Peng Cui, Aapo Hyvärinen:
Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), San Diego, CA, USA, 24 August 2020. Proceedings of Machine Learning Research 127, PMLR 2020 [contents] - [e4]Yong Man Ro, Wen-Huang Cheng, Junmo Kim, Wei-Ta Chu, Peng Cui, Jung-Woo Choi, Min-Chun Hu, Wesley De Neve:
MultiMedia Modeling - 26th International Conference, MMM 2020, Daejeon, South Korea, January 5-8, 2020, Proceedings, Part I. Lecture Notes in Computer Science 11961, Springer 2020, ISBN 978-3-030-37730-4 [contents] - [e3]Yong Man Ro, Wen-Huang Cheng, Junmo Kim, Wei-Ta Chu, Peng Cui, Jung-Woo Choi, Min-Chun Hu, Wesley De Neve:
MultiMedia Modeling - 26th International Conference, MMM 2020, Daejeon, South Korea, January 5-8, 2020, Proceedings, Part II. Lecture Notes in Computer Science 11962, Springer 2020, ISBN 978-3-030-37733-5 [contents] - [i31]Wenwu Zhu, Xin Wang, Peng Cui:
Deep Learning for Learning Graph Representations. CoRR abs/2001.00293 (2020) - [i30]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction with Model Misspecification and Agnostic Distribution Shift. CoRR abs/2001.11713 (2020) - [i29]Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui:
Structural Deep Clustering Network. CoRR abs/2002.01633 (2020) - [i28]Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi:
A Semi-supervised Graph Attentive Network for Financial Fraud Detection. CoRR abs/2003.01171 (2020) - [i27]Linjun Zhou, Peng Cui, Xu Jia, Shiqiang Yang, Qi Tian:
Learning to Select Base Classes for Few-shot Classification. CoRR abs/2004.00315 (2020) - [i26]Ziwei Zhang, Peng Cui, Jian Pei, Xin Wang, Wenwu Zhu:
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs. CoRR abs/2006.04330 (2020) - [i25]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Invariant Adversarial Learning for Distributional Robustness. CoRR abs/2006.04414 (2020) - [i24]Kun Kuang, Bo Li, Peng Cui, Yue Liu, Jianrong Tao, Yueting Zhuang, Fei Wu:
Stable Prediction via Leveraging Seed Variable. CoRR abs/2006.05076 (2020) - [i23]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. CoRR abs/2006.10483 (2020) - [i22]Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. CoRR abs/2007.02265 (2020) - [i21]Linjun Zhou, Peng Cui, Yinan Jiang, Shiqiang Yang:
Adversarial Eigen Attack on Black-Box Models. CoRR abs/2009.00097 (2020) - [i20]Ziwei Zhang, Chenhao Niu, Peng Cui, Bo Zhang, Wei Cui, Wenwu Zhu:
A Simple and General Graph Neural Network with Stochastic Message Passing. CoRR abs/2009.02562 (2020) - [i19]Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui:
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation. CoRR abs/2010.12408 (2020)
2010 – 2019
- 2019
- [j35]Yitian Yuan
, Tao Mei
, Peng Cui
, Wenwu Zhu
:
Video Summarization by Learning Deep Side Semantic Embedding. IEEE Trans. Circuits Syst. Video Technol. 29(1): 226-237 (2019) - [j34]Jiuyong Li
, Kun Zhang, Emre Kiciman, Peng Cui:
Introduction to the Special Section on Advances in Causal Discovery and Inference. ACM Trans. Intell. Syst. Technol. 10(5): 45:1-45:3 (2019) - [j33]Peng Cui
, Xiao Wang, Jian Pei
, Wenwu Zhu
:
A Survey on Network Embedding. IEEE Trans. Knowl. Data Eng. 31(5): 833-852 (2019) - [c89]