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ORCIDPeng 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
![[0000-0001-9168-170X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-9168-170X")
— 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]