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ORCIDPeng Cui 0001
Person information
- affiliation (PhD 2010): Tsinghua University, Department of Computer Science and Technology, Beijing, China
- not to be confused with: Peng Cui 0007
Other persons with the same name
- Peng Cui — disambiguation page
- Peng Cui 0002
![[0000-0001-9168-170X]](https://dblp.uni-trier.de./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
- Peng Cui 0007 — Tsinghua University, Department of Computer Science and Technology, BNRist, THU-Bosch Joint ML Center, Beijing, China
- Peng Cui 0008 — Renmin University of China, School of Information Resource Management, Beijing, China
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Journal Articles
- 2024
[j62]Bing Yuan, Jiang Zhang, Aobo Lyu, Jiayun Wu, Zhipeng Wang, Mingzhe Yang, Kaiwei Liu, Muyun Mou, Peng Cui:
Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies. Entropy 26(2): 108 (2024)- [j61]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-of-Distribution Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 322-337 (2024) - [j60]Shixuan Liu, Changjun Fan, Kewei Cheng, Yunfei Wang, Peng Cui, Yizhou Sun, Zhong Liu:
Inductive Meta-Path Learning for Schema-Complex Heterogeneous Information Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 10196-10209 (2024) - [j59]Huacheng Li, Chunhe Xia, Tianbo Wang, Zhao Wang, Peng Cui, Xiaojian Li:
GRASS: Learning Spatial-Temporal Properties From Chainlike Cascade Data for Microscopic Diffusion Prediction. IEEE Trans. Neural Networks Learn. Syst. 35(11): 16313-16327 (2024) - 2023
- [j58]Ziyu Zhao, 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) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [j53]Xiangmeng Wang, Qian Li, Dianer Yu, Peng Cui, Zhichao Wang, Guandong Xu:
Causal Disentanglement for Semantic-Aware Intent Learning in Recommendation. IEEE Trans. Knowl. Data Eng. 35(10): 9836-9849 (2023) - [j52]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning With Stable Adversarial Training. IEEE Trans. Knowl. Data Eng. 35(11): 11288-11300 (2023) - [j51]Jianxin Li, Lifang He, Hao Peng, Peng Cui, Charu C. Aggarwal, Philip S. Yu:
Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. IEEE Trans. Knowl. Data Eng. 35(12): 11982-11983 (2023) - [j50]Xumin Chen, Ruobing Xie, Zhijie Qiu, Peng Cui, Ziwei Zhang, Shukai Liu, Shiqiang Yang, Bo Zhang, Leyu Lin:
Group-based social diffusion in recommendation. World Wide Web (WWW) 26(4): 1775-1792 (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) - 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) - 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) - 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) - 2018
- [j32]Kun Kuang, Meng Jiang, Peng Cui, Hengliang Luo, Shiqiang Yang:
Effective Promotional Strategies Selection in Social Media: A Data-Driven Approach. IEEE Trans. Big Data 4(4): 487-501 (2018) - [j31]Chengxi Zang, Peng Cui, Christos Faloutsos, Wenwu Zhu:
On Power Law Growth of Social Networks. IEEE Trans. Knowl. Data Eng. 30(9): 1727-1740 (2018) - [j30]Dingyuan Zhu, Peng Cui, Ziwei Zhang, Jian Pei, Wenwu Zhu:
High-Order Proximity Preserved Embedding for Dynamic Networks. IEEE Trans. Knowl. Data Eng. 30(11): 2134-2144 (2018) - [j29]Peng Cui, Shaowei Liu, Wenwu Zhu:
General Knowledge Embedded Image Representation Learning. IEEE Trans. Multim. 20(1): 198-207 (2018) - 2017
- [j28]Ting Rui, Peng Cui, Wenwu Zhu:
Joint user-interest and social-influence emotion prediction for individuals. Neurocomputing 230: 66-76 (2017) - [j27]Linyun Yu, Peng Cui, Fei Wang, Chaoming Song, Shiqiang Yang:
Uncovering and predicting the dynamic process of information cascades with survival model. Knowl. Inf. Syst. 50(2): 633-659 (2017) - [j26]Wu Liu, Peng Cui, Jukka K. Nurminen, Jingdong Wang:
Special issue on intelligent urban computing with big data. Mach. Vis. Appl. 28(7): 675-677 (2017) - [j25]Tianyang Zhang, Peng Cui, Christos Faloutsos, Yunfei Lu, Hao Ye, Wenwu Zhu, Shiqiang Yang:
comeNgo: A Dynamic Model for Social Group Evolution. ACM Trans. Knowl. Discov. Data 11(4): 41:1-41:22 (2017) - 2016
- [j24]Peng Cui, Huan Liu, Charu C. Aggarwal, Fei Wang:
Online Behavioral Analysis and Modeling [Guest Editorial]. IEEE Intell. Syst. 31(1): 2-4 (2016) - [j23]Meng Jiang, Peng Cui, Christos Faloutsos:
Suspicious Behavior Detection: Current Trends and Future Directions. IEEE Intell. Syst. 31(1): 31-39 (2016) - [j22]Peng Cui, Huan Liu, Charu C. Aggarwal, Fei Wang:
Uncovering and Predicting Human Behaviors. IEEE Intell. Syst. 31(2): 77-88 (2016) - [j21]Peng Cui, Wenwu Zhu, Tat-Seng Chua, Ramesh C. Jain:
Social-Sensed Multimedia Computing. IEEE Multim. 23(1): 92-96 (2016) - [j20]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Inferring lockstep behavior from connectivity pattern in large graphs. Knowl. Inf. Syst. 48(2): 399-428 (2016) - [j19]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Catching Synchronized Behaviors in Large Networks: A Graph Mining Approach. ACM Trans. Knowl. Discov. Data 10(4): 35:1-35:27 (2016) - [j18]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms. IEEE Trans. Knowl. Data Eng. 28(8): 2187-2200 (2016) - 2015
- [j17]Wenwu Zhu, Peng Cui, Zhi Wang, Gang Hua:
Multimedia Big Data Computing. IEEE Multim. 22(3): 96- (2015) - [j16]Meng Jiang, Peng Cui, Xumin Chen, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Social Recommendation with Cross-Domain Transferable Knowledge. IEEE Trans. Knowl. Data Eng. 27(11): 3084-3097 (2015) - [j15]Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu:
Learning Compact Hash Codes for Multimodal Representations Using Orthogonal Deep Structure. IEEE Trans. Multim. 17(9): 1404-1416 (2015) - 2014
- [j14]Shaowei Liu, Peng Cui, Huan-Bo Luan, Wenwu Zhu, Shiqiang Yang, Qi Tian:
Social-oriented visual image search. Comput. Vis. Image Underst. 118: 30-39 (2014) - [j13]Dan Xu, Peng Cui, Wenwu Zhu, Shiqiang Yang:
Graph-Based Residence Location Inference for Social Media Users. IEEE Multim. 21(4): 76-83 (2014) - [j12]Zhiyu Wang, Peng Cui, Fangtao Li, Edward Y. Chang, Shiqiang Yang:
A data-driven study of image feature extraction and fusion. Inf. Sci. 281: 536-558 (2014) - [j11]Yue Gao, Rongrong Ji, Peng Cui, Qionghai Dai, Gang Hua:
Hyperspectral Image Classification Through Bilayer Graph-Based Learning. IEEE Trans. Image Process. 23(7): 2769-2778 (2014) - [j10]Meng Jiang, Peng Cui, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Scalable Recommendation with Social Contextual Information. IEEE Trans. Knowl. Data Eng. 26(11): 2789-2802 (2014) - [j9]Peng Cui, Shaowei Liu, Wenwu Zhu, Huan-Bo Luan, Tat-Seng Chua, Shi-Qiang Yang:
Social-Sensed Image Search. ACM Trans. Inf. Syst. 32(2): 8:1-8:23 (2014) - [j8]Zhiyu Wang, Peng Cui, Lexing Xie, Wenwu Zhu, Yong Rui, Shiqiang Yang:
Bilateral Correspondence Model for Words-and-Pictures Association in Multimedia-Rich Microblogs. ACM Trans. Multim. Comput. Commun. Appl. 10(4): 34:1-34:21 (2014) - 2013
- [j7]Zhi Wang, Wenwu Zhu, Xiangwen Chen, Lifeng Sun, Jiangchuan Liu, Minghua Chen, Peng Cui, Shiqiang Yang:
Propagation-based social-aware multimedia content distribution. ACM Trans. Multim. Comput. Commun. Appl. 9(1s): 52:1-52:20 (2013) - 2012
- [j6]Fei Wang, Peng Cui, Gordon Sun, Tat-Seng Chua, Shiqiang Yang:
Guest editorial: Special issue on information retrieval for social media. Inf. Retr. 15(3-4): 179-182 (2012) - [j5]Chao Wang, Lifeng Sun, Peng Cui, Jianwei Zhang, Shiqiang Yang:
Analyzing Image Deblurring Through Three Paradigms. IEEE Trans. Image Process. 21(1): 115-129 (2012) - [j4]Peng Cui, Fei Wang, Lifeng Sun, Jianwei Zhang, Shi-Qiang Yang:
A Matrix-Based Approach to Unsupervised Human Action Categorization. IEEE Trans. Multim. 14(1): 102-110 (2012) - 2011
- [j3]Peng Cui, Zhi-Qiang Liu, Lifeng Sun, Shi-Qiang Yang:
Hierarchical visual event pattern mining and its applications. Data Min. Knowl. Discov. 22(3): 467-492 (2011) - 2009
- [j2]Peng Cui, Lifeng Sun, Shiqiang Yang:
Adaptive mixture observation models for multiple object tracking. Sci. China Ser. F Inf. Sci. 52(2): 226-235 (2009) - [j1]Peng Cui, Lifeng Sun, Fei Wang, Shiqiang Yang:
Contextual Mixture Tracking. IEEE Trans. Multim. 11(2): 333-341 (2009)
Conference and Workshop Papers
- 2024
- [c168]Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui:
Enhancing Distributional Stability among Sub-populations. AISTATS 2024: 2125-2133 - [c167]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CVPR 2024: 21897-21908 - [c166]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. ICLR 2024 - [c165]Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, Peng Cui:
Domain-wise Data Acquisition to Improve Performance under Distribution Shift. ICML 2024 - [c164]José H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu:
Stability Evaluation through Distributional Perturbation Analysis. ICML 2024 - [c163]Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui:
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. ICML 2024 - [c162]Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui:
Model-Agnostic Random Weighting for Out-of-Distribution Generalization. KDD 2024: 1050-1061 - [c161]Wenjing Yang, Haotian Wang, Haoxuan Li, Hao Zou, Ruochun Jin, Kun Kuang, Peng Cui:
Your Neighbor Matters: Towards Fair Decisions Under Networked Interference. KDD 2024: 3829-3840 - [c160]Qingsong Wen, Jing Liang, Carles Sierra, Rose Luckin, Richard Jiarui Tong, Zitao Liu, Peng Cui, Jiliang Tang:
AI for Education (AI4EDU): Advancing Personalized Education with LLM and Adaptive Learning. KDD 2024: 6743-6744 - 2023
- [c159]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. AAAI 2023: 10998-11006 - [c158]Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui:
Covariate-Shift Generalization via Random Sample Weighting. AAAI 2023: 11828-11836 - [c157]Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui:
Factual Observation Based Heterogeneity Learning for Counterfactual Prediction. CLeaR 2023: 350-370 - [c156]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CVPR 2023: 16036-16047 - [c155]Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui:
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CVPR 2023: 20247-20257 - [c154]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 - [c153]Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui:
Flatness-Aware Minimization for Domain Generalization. ICCV 2023: 5166-5179 - [c152]Haoyang Li, Xin Wang, Ziwei Zhang, Jianxin Ma, Peng Cui, Wenwu Zhu:
Intention-aware Sequential Recommendation with Structured Intent Transition : (Extended Abstract). ICDE 2023: 3759-3760 - [c151]Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui:
Measure the Predictive Heterogeneity. ICLR 2023 - [c150]Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui:
Propensity Matters: Measuring and Enhancing Balancing for Recommendation. ICML 2023: 20182-20194 - [c149]Xiaoyu Tan, Lin Yong, Shengyu Zhu, Chao Qu, Xihe Qiu, Yinghui Xu, Peng Cui, Yuan Qi:
Provably Invariant Learning without Domain Information. ICML 2023: 33563-33580 - [c148]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. ICML 2023: 38674-38706 - [c147]Haoxuan Li, Chunyuan Zheng, Peng Wu, Kun Kuang, Yue Liu, Peng Cui:
Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. KDD 2023: 1235-1247 - [c146]Yu Xiong, Runze Wu, Shiwei Zhao, Jianrong Tao, Xudong Shen, Tangjie Lyu, Changjie Fan, Peng Cui:
A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games. KDD 2023: 5303-5314 - [c145]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2023: 5831-5832 - [c144]Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
Preface: The 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision. CDPD 2023: 1-2 - [c143]Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong:
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets. NeurIPS 2023 - [c142]Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu:
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [c141]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 - 2022
- [c140]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Towards Unsupervised Domain Generalization. CVPR 2022: 4900-4910 - [c139]Linjun Zhou, Peng Cui, Xingxuan Zhang, Yinan Jiang, Shiqiang Yang:
Adversarial Eigen Attack on BlackBox Models. CVPR 2022: 15233-15241 - [c138]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 - [c137]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 - [c136]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 - [c135]Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding, Peng Cui:
Counterfactual Prediction for Outcome-Oriented Treatments. ICML 2022: 27693-27706 - [c134]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 - [c133]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 - [c132]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 - [c131]Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao, Xiaojie Guo:
Graph Neural Networks: Foundation, Frontiers and Applications. KDD 2022: 4840-4841 - [c130]Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui:
ZIN: When and How to Learn Invariance Without Environment Partition? NeurIPS 2022 - [c129]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Distributionally Robust Optimization with Data Geometry. NeurIPS 2022 - [c128]Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui:
Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS 2022 - [c127]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. WWW 2022: 4-15 - [c126]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 - 2021
- [c125]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 - [c124]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Stable Adversarial Learning under Distributional Shifts. AAAI 2021: 8662-8670 - [c123]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 - [c122]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-of-Distribution Generalization. CVPR 2021: 5372-5382 - [c121]Yijian Qin, Xin Wang, Peng Cui, Wenwu Zhu:
GQNAS: Graph Q Network for Neural Architecture Search. ICDM 2021: 1288-1293 - [c120]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. ICML 2021: 6804-6814 - [c119]Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang:
DARING: Differentiable Causal Discovery with Residual Independence. KDD 2021: 596-605 - [c118]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 - [c117]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 - [c116]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 - [c115]Xin Wang, Peng Cui, Wenwu Zhu:
Out-of-distribution Generalization and Its Applications for Multimedia. ACM Multimedia 2021: 5681-5682 - [c114]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. NeurIPS 2021: 21720-21731 - [c113]Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi:
Temporal-Aware Graph Neural Network for Credit Risk Prediction. SDM 2021: 702-710 - [c112]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. WWW 2021: 1215-1226 - [c111]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 - 2020
- [c110]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 - [c109]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 - [c108]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction with Model Misspecification and Agnostic Distribution Shift. AAAI 2020: 4485-4492 - [c107]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. AAAI 2020: 5692-5699 - [c106]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 - [c105]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 - [c104]Linjun Zhou, Peng Cui, Xu Jia, Shiqiang Yang, Qi Tian:
Learning to Select Base Classes for Few-Shot Classification. CVPR 2020: 4623-4632 - [c103]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 - [c102]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 - [c101]Jianxin Ma, Chang Zhou, Hongxia Yang, Peng Cui, Xin Wang, Wenwu Zhu:
Disentangled Self-Supervision in Sequential Recommenders. KDD 2020: 483-491 - [c100]Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. KDD 2020: 1243-1253 - [c99]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. KDD 2020: 2125-2135 - [c98]Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. KDD 2020: 2185-2193 - [c97]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 - [c96]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 - [c95]Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao:
Causal Inference Meets Machine Learning. KDD 2020: 3527-3528 - [c94]Fei Wang, Peng Cui, Jian Pei, Yangqiu Song, Chengxi Zang:
Recent Advances on Graph Analytics and Its Applications in Healthcare. KDD 2020: 3545-3546 - [c93]Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He:
Counterfactual Prediction for Bundle Treatment. NeurIPS 2020 - [c92]Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui:
Structural Deep Clustering Network. WWW 2020: 1400-1410 - 2019
- [c91]Linjun Zhou, Peng Cui, Shiqiang Yang, Wenwu Zhu, Qi Tian:
Learning to Learn Image Classifiers With Visual Analogy. CVPR 2019: 11497-11506 - [c90]Yuzhen Tong, Yadan Luo, Zheng Zhang, Shazia W. Sadiq, Peng Cui:
Collaborative Generative Adversarial Network for Recommendation Systems. ICDE Workshops 2019: 161-168 - [c89]Yang Li, Yadan Luo, Zheng Zhang, Shazia W. Sadiq, Peng Cui:
Context-Aware Attention-Based Data Augmentation for POI Recommendation. ICDE Workshops 2019: 177-184 - [c88]Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang:
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection. ICDM 2019: 598-607 - [c87]Zhixiu Liu, Chengxi Zang, Kun Kuang, Hao Zou, Hu Zheng, Peng Cui:
Causation-Driven Visualizations for Insurance Recommendation. ICME Workshops 2019: 471-476 - [c86]Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, Wenwu Zhu:
Disentangled Graph Convolutional Networks. ICML 2019: 4212-4221 - [c85]Shengze Yu, Xin Wang, Wenwu Zhu, Peng Cui, Jingdong Wang:
Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation. IJCAI 2019: 4635-4641 - [c84]Thuc Duy Le, Jiuyong Li, Kun Zhang, Emre Kiciman, Peng Cui, Aapo Hyvärinen:
Preface: The 2019 ACM SIGKDD Workshop on Causal Discovery. CD@KDD 2019: 1-3 - [c83]Ke Tu, Jianxin Ma, Peng Cui, Jian Pei, Wenwu Zhu:
AutoNE: Hyperparameter Optimization for Massive Network Embedding. KDD 2019: 216-225 - [c82]Chengxi Zang, Peng Cui, Wenwu Zhu, Fei Wang:
Dynamical Origins of Distribution Functions. KDD 2019: 469-478 - [c81]Haoyang Li, Peng Cui, Chengxi Zang, Tianyang Zhang, Wenwu Zhu, Yishi Lin:
Fates of Microscopic Social Ecosystems: Keep Alive or Dead? KDD 2019: 668-676 - [c80]Hao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui:
Focused Context Balancing for Robust Offline Policy Evaluation. KDD 2019: 696-704 - [c79]Dingyuan Zhu, Ziwei Zhang, Peng Cui, Wenwu Zhu:
Robust Graph Convolutional Networks Against Adversarial Attacks. KDD 2019: 1399-1407 - [c78]Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu, Fei Wang:
Uncovering Pattern Formation of Information Flow. KDD 2019: 1691-1699 - [c77]Jianrong Tao, Jianshi Lin, Shize Zhang, Sha Zhao, Runze Wu, Changjie Fan, Peng Cui:
MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games. KDD 2019: 2536-2546 - [c76]Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu:
Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena. KDD 2019: 3093-3101 - [c75]Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu:
Learning From Networks: Algorithms, Theory, and Applications. KDD 2019: 3221-3222 - [c74]Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang, Wenwu Zhu:
Learning Disentangled Representations for Recommendation. NeurIPS 2019: 5712-5723 - [c73]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Yanfang Ye, Peng Cui, Philip S. Yu:
Heterogeneous Graph Attention Network. WWW 2019: 2022-2032 - 2018
- [c72]Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu:
TIMERS: Error-Bounded SVD Restart on Dynamic Networks. AAAI 2018: 224-231 - [c71]Jianxin Ma, Peng Cui, Wenwu Zhu:
DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks. AAAI 2018: 370-377 - [c70]Ke Tu, Peng Cui, Xiao Wang, Fei Wang, Wenwu Zhu:
Structural Deep Embedding for Hyper-Networks. AAAI 2018: 426-433 - [c69]Daixin Wang, Peng Cui, Wenwu Zhu:
Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation. AAAI 2018: 443-450 - [c68]Yunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu:
Collective Human Behavior in Cascading System: Discovery, Modeling and Applications. ICDM 2018: 297-306 - [c67]Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, Wenwu Zhu:
Billion-Scale Network Embedding with Iterative Random Projection. ICDM 2018: 787-796 - [c66]Xiao Wang, Ziwei Zhang, Jing Wang, Peng Cui, Shiqiang Yang:
Power-law Distribution Aware Trust Prediction. IJCAI 2018: 3564-3570 - [c65]Xumin Chen, Peng Cui, Lingling Yi, Shiqiang Yang:
Scalable Optimization for Embedding Highly-Dynamic and Recency-Sensitive Data. KDD 2018: 130-138 - [c64]Kun Kuang, Peng Cui, Susan Athey, Ruoxuan Xiong, Bo Li:
Stable Prediction across Unknown Environments. KDD 2018: 1617-1626 - [c63]Jianxin Ma, Peng Cui, Xiao Wang, Wenwu Zhu:
Hierarchical Taxonomy Aware Network Embedding. KDD 2018: 1920-1929 - [c62]Ke Tu, Peng Cui, Xiao Wang, Philip S. Yu, Wenwu Zhu:
Deep Recursive Network Embedding with Regular Equivalence. KDD 2018: 2357-2366 - [c61]Chengxi Zang, Peng Cui, Wenwu Zhu:
Learning and Interpreting Complex Distributions in Empirical Data. KDD 2018: 2682-2691 - [c60]Ziwei Zhang, Peng Cui, Xiao Wang, Jian Pei, Xuanrong Yao, Wenwu Zhu:
Arbitrary-Order Proximity Preserved Network Embedding. KDD 2018: 2778-2786 - [c59]Dingyuan Zhu, Peng Cui, Daixin Wang, Wenwu Zhu:
Deep Variational Network Embedding in Wasserstein Space. KDD 2018: 2827-2836 - [c58]Peng Cui:
Session details: FF-2. ACM Multimedia 2018 - [c57]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, Peixuan Chen:
Causally Regularized Learning with Agnostic Data Selection Bias. ACM Multimedia 2018: 411-419 - [c56]Jitao Sang, Jun Yu, Ramesh C. Jain, Rainer Lienhart, Peng Cui, Jiashi Feng:
Deep Learning for Multimedia: Science or Technology? ACM Multimedia 2018: 1354-1355 - 2017
- [c55]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, Fei Wang:
Treatment Effect Estimation with Data-Driven Variable Decomposition. AAAI 2017: 140-146 - [c54]Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang:
Community Preserving Network Embedding. AAAI 2017: 203-209 - [c53]Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang:
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing. KDD 2017: 265-274 - [c52]Chengxi Zang, Peng Cui, Christos Faloutsos, Wenwu Zhu:
Long Short Memory Process: Modeling Growth Dynamics of Microscopic Social Connectivity. KDD 2017: 565-574 - [c51]Linyun Yu, Peng Cui, Chaoming Song, Tianyang Zhang, Shiqiang Yang:
A Temporally Heterogeneous Survival Framework with Application to Social Behavior Dynamics. KDD 2017: 1295-1304 - [c50]Peng Cui, Wenwu Zhu:
Human-like Visual Learning and Reasoning. ACM Multimedia 2017: 1951-1952 - [c49]Chengxi Zang, Peng Cui, Chaoming Song, Christos Faloutsos, Wenwu Zhu:
Quantifying Structural Patterns of Information Cascades. WWW (Companion Volume) 2017: 867-868 - 2016
- [c48]Meng Jiang, Peng Cui, Nicholas Jing Yuan, Xing Xie, Shiqiang Yang:
Little Is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds. AAAI 2016: 13-19 - [c47]Kun Kuang, Meng Jiang, Peng Cui, Shiqiang Yang:
Steering Social Media Promotions with Effective Strategies. ICDM 2016: 985-990 - [c46]Mingdong Ou, Peng Cui, Jian Pei, Ziwei Zhang, Wenwu Zhu:
Asymmetric Transitivity Preserving Graph Embedding. KDD 2016: 1105-1114 - [c45]Daixin Wang, Peng Cui, Wenwu Zhu:
Structural Deep Network Embedding. KDD 2016: 1225-1234 - [c44]Tianyang Zhang, Peng Cui, Christos Faloutsos, Yunfei Lu, Hao Ye, Wenwu Zhu, Shiqiang Yang:
Come-and-Go Patterns of Group Evolution: A Dynamic Model. KDD 2016: 1355-1364 - [c43]Chengxi Zang, Peng Cui, Christos Faloutsos:
Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications. KDD 2016: 2015-2024 - [c42]Jie Nie, Lei Huang, Peng Cui, Zhen Li, Yan Yan, Zhiqiang Wei, Wenwu Zhu:
Social Media Profiler: Inferring Your Social Media Personality from Visual Attributes in Portrait. PCM (2) 2016: 640-649 - 2015
- [c41]Peng Cui, Tianyang Zhang, Fei Wang, Peng He:
Perceiving Group Themes from Collective Social and Behavioral Information. AAAI 2015: 65-71 - [c40]Mingdong Ou, Peng Cui, Jun Wang, Fei Wang, Wenwu Zhu:
Probabilistic Attributed Hashing. AAAI 2015: 2894-2900 - [c39]Ting Rui, Jianchao Fei, Peng Cui, You Zhou, Husheng Fang:
Head detection based on convolutional neural network with multi-stage weighted feature. ChinaSIP 2015: 147-150 - [c38]Linyun Yu, Peng Cui, Fei Wang, Chaoming Song, Shiqiang Yang:
From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics. ICDM 2015: 559-568 - [c37]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
A General Suspiciousness Metric for Dense Blocks in Multimodal Data. ICDM 2015: 781-786 - [c36]Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu:
Deep Multimodal Hashing with Orthogonal Regularization. IJCAI 2015: 2291-2297 - [c35]Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu:
Non-transitive Hashing with Latent Similarity Components. KDD 2015: 895-904 - [c34]Shaowei Liu, Peng Cui, Wenwu Zhu, Shiqiang Yang:
Learning Socially Embedded Visual Representation from Scratch. ACM Multimedia 2015: 109-118 - 2014
- [c33]Jingyuan Wang, Fei Gao, Peng Cui, Chao Li, Zhang Xiong:
Discovering Urban Spatio-temporal Structure from Time-Evolving Traffic Networks. APWeb 2014: 93-104 - [c32]Dan Xu, Peng Cui, Wenwu Zhu, Shiqiang Yang:
Find you from your friends: Graph-based residence location prediction for users in social media. ICME 2014: 1-6 - [c31]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
CatchSync: catching synchronized behavior in large directed graphs. KDD 2014: 941-950 - [c30]Meng Jiang, Peng Cui, Fei Wang, Xinran Xu, Wenwu Zhu, Shiqiang Yang:
FEMA: flexible evolutionary multi-faceted analysis for dynamic behavioral pattern discovery. KDD 2014: 1186-1195 - [c29]Yun Yang, Peng Cui, Wenwu Zhu, H. Vicky Zhao, Yuanyuan Shi, Shiqiang Yang:
Emotionally Representative Image Discovery for Social Events. ICMR 2014: 177 - [c28]Peng Cui, Zhiyu Wang, Zhou Su:
What Videos Are Similar with You?: Learning a Common Attributed Representation for Video Recommendation. ACM Multimedia 2014: 597-606 - [c27]Shaowei Liu, Peng Cui, Wenwu Zhu, Shiqiang Yang, Qi Tian:
Social Embedding Image Distance Learning. ACM Multimedia 2014: 617-626 - [c26]Jie Nie, Peng Cui, Yan Yan, Lei Huang, Zhen Li, Zhiqiang Wei:
How Your Portrait Impresses People?: Inferring Personality Impressions from Portrait Contents. ACM Multimedia 2014: 905-908 - [c25]Peng Cui, Lexing Xie, Jitao Sang, Changsheng Xu:
Social multimedia computing. ACM Multimedia 2014: 1237-1238 - [c24]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Inferring Strange Behavior from Connectivity Pattern in Social Networks. PAKDD (1) 2014: 126-138 - [c23]Peng Cui, Fei Wang, Hanghang Tong, Manuel Gomez-Rodriguez:
1st workshop on diffusion networks and cascade analytics. WSDM 2014: 689-690 - [c22]Meng Jiang, Peng Cui, Alex Beutel, Christos Faloutsos, Shiqiang Yang:
Detecting suspicious following behavior in multimillion-node social networks. WWW (Companion Volume) 2014: 305-306 - 2013
- [c21]Hao Chen, Han Tang, Zhiyu Wang, Peng Cui, Yingquing Xu, Shiqiang Yang:
EventLens: An Automatic Magazine Generating System for Social Media. HCI (13) 2013: 177-186 - [c20]Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu, Shiqiang Yang:
Comparing apples to oranges: a scalable solution with heterogeneous hashing. KDD 2013: 230-238 - [c19]Peng Cui, Shifei Jin, Linyun Yu, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Cascading outbreak prediction in networks: a data-driven approach. KDD 2013: 901-909 - [c18]Tao Chen, Dongyuan Lu, Min-Yen Kan, Peng Cui:
Understanding and classifying image tweets. ACM Multimedia 2013: 781-784 - [c17]Yun Yang, Peng Cui, Wenwu Zhu, Shiqiang Yang:
User interest and social influence based emotion prediction for individuals. ACM Multimedia 2013: 785-788 - [c16]Shaowei Liu, Peng Cui, Huan-Bo Luan, Wenwu Zhu, Shiqiang Yang, Qi Tian:
Social Visual Image Ranking for Web Image Search. MMM (1) 2013: 239-249 - [c15]Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui:
Multimedia recommendation: technology and techniques. SIGIR 2013: 1131 - 2012
- [c14]Meng Jiang, Peng Cui, Rui Liu, Qiang Yang, Fei Wang, Wenwu Zhu, Shiqiang Yang:
Social contextual recommendation. CIKM 2012: 45-54 - [c13]Meng Jiang, Peng Cui, Fei Wang, Qiang Yang, Wenwu Zhu, Shiqiang Yang:
Social recommendation across multiple relational domains. CIKM 2012: 1422-1431 - [c12]Zhiyu Wang, Peng Cui, Lexing Xie, Hao Chen, Wenwu Zhu, Shiqiang Yang:
Analyzing social media via event facets. ACM Multimedia 2012: 1359-1360 - [c11]Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui:
Multimedia recommendation. ACM Multimedia 2012: 1535-1536 - 2011
- [c10]Peng Cui, Fei Wang, Shiqiang Yang, Lifeng Sun:
Item-Level Social Influence Prediction with Probabilistic Hybrid Factor Matrix Factorization. AAAI 2011: 331-336 - [c9]Xin Li, Xia Zhang, Peng Cui, Zhiyong Fu, Shiqiang Yang, Baoguo Cui:
The Visualization of Mass Information in Social Network with a Holistic View. EVA 2011 - [c8]Naeem Ramzan, Fei Wang, Charalampos Z. Patrikakis, Peng Cui, Nikolaos D. Doulamis, Shiqiang Yang, Gordon Sun:
ACM international workshop on social and behavioral networked media access (SBNMA'11). ACM Multimedia 2011: 611-612 - [c7]Peng Cui, Fei Wang, Shaowei Liu, Mingdong Ou, Shiqiang Yang, Lifeng Sun:
Who should share what?: item-level social influence prediction for users and posts ranking. SIGIR 2011: 185-194 - 2010
- [c6]Yin-Jun Miao, Chao Wang, Peng Cui, Lifeng Sun, Pin Tao, Shiqiang Yang:
HFAG: Hierarchical Frame Affinity Group for video retrieval on very large video dataset. ICIP 2010: 1041-1044 - 2009
- [c5]Xi-Feng Ding, Hui Xu, Peng Cui, Lifeng Sun, Shiqiang Yang:
A Cascade SVM Approach for Head-shoulder Detection using Histograms of Oriented Gradients. ISCAS 2009: 1791-1794 - 2008
- [c4]Peng Cui, Fei Wang, Lifeng Sun, Shi-Qiang Yang:
A Joint Matrix Factorization Approach to Unsupervised Action Categorization. ICDM 2008: 767-772 - [c3]Zhuoyuan Chen, Peng Cui, Lifeng Sun, Shiqiang Yang:
Analysis of Human Actions for Video Indexing. PCM 2008: 635-642 - 2007
- [c2]Peng Cui, Lifeng Sun, Zhi-Qiang Liu, Shiqiang Yang:
A Sequential Monte Carlo Approach to Anomaly Detection in Tracking Visual Events. CVPR 2007 - [c1]Peng Cui, Lifeng Sun, Zhi Wang, Shi-Qiang Yang:
A Novel Event-Oriented Segment-of-Interest Discovery Method for Surveillance Video. ICME 2007: 823-826
Parts in Books or Collections
- 2018
- [p2]Peng Cui:
Social-sensed multimedia computing. Frontiers of Multimedia Research 2018: 137-157 - 2013
- [p1]Zhi Wang, Wenwu Zhu, Peng Cui, Lifeng Sun, Shiqiang Yang:
Social Media Recommendation. Social Media Retrieval 2013: 23-42
Editorship
- 2023
- [e6]Thuc Duy Le, Jiuyong Li, Robert Ness, Sofia Triantafillou, Shohei Shimizu, Peng Cui, Kun Kuang, Jian Pei, Fei Wang, Mattia Prosperi:
The KDD'23 Workshop on Causal Discovery, Prediction and Decision, 07 August 2023, Long Beach, CA, USA. Proceedings of Machine Learning Research 218, PMLR 2023 [contents] - 2020
- [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] - 2019
- [e2]Wenwu Zhu, Dacheng Tao, Xueqi Cheng, Peng Cui, Elke A. Rundensteiner, David Carmel, Qi He, Jeffrey Xu Yu:
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM 2019, Beijing, China, November 3-7, 2019. ACM 2019, ISBN 978-1-4503-6976-3 [contents] - [e1]Thuc Duy Le, Jiuyong Li, Kun Zhang, Emre Kiciman, Peng Cui, Aapo Hyvärinen:
Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, CD@KDD 2019, Anchorage, Alaska, USA, August 5, 2019. Proceedings of Machine Learning Research 104, PMLR 2019 [contents]
Informal and Other Publications
- 2024
- [i74]Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Peng Cui:
On the Out-Of-Distribution Generalization of Multimodal Large Language Models. CoRR abs/2402.06599 (2024) - [i73]Han Yu, Jiashuo Liu, Xingxuan Zhang, Jiayun Wu, Peng Cui:
A Survey on Evaluation of Out-of-Distribution Generalization. CoRR abs/2403.01874 (2024) - [i72]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators. CoRR abs/2403.15524 (2024) - [i71]Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui:
Debiased Collaborative Filtering with Kernel-Based Causal Balancing. CoRR abs/2404.19596 (2024) - [i70]Jose H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu:
Stability Evaluation via Distributional Perturbation Analysis. CoRR abs/2405.03198 (2024) - [i69]Jiayun Wu, Jiashuo Liu, Peng Cui, Zhiwei Steven Wu:
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift. CoRR abs/2406.00661 (2024) - 2023
- [i68]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) - [i67]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) - [i66]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Predictive Heterogeneity: Measures and Applications. CoRR abs/2304.00305 (2023) - [i65]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CoRR abs/2305.15253 (2023) - [i64]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) - [i63]Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu:
Meta Adaptive Task Sampling for Few-Domain Generalization. CoRR abs/2305.15644 (2023) - [i62]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) - [i61]Shixuan Liu, Changjun Fan, Kewei Cheng, Yunfei Wang, Peng Cui, Yizhou Sun, Zhong Liu:
Inductive Meta-path Learning for Schema-complex Heterogeneous Information Networks. CoRR abs/2307.03937 (2023) - [i60]Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong:
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets. CoRR abs/2307.05284 (2023) - [i59]Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui:
Flatness-Aware Minimization for Domain Generalization. CoRR abs/2307.11108 (2023) - [i58]Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui:
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. CoRR abs/2311.05054 (2023) - [i57]Bing Yuan, Zhang Jiang, Aobo Lyu, Jiayun Wu, Zhipeng Wang, Mingzhe Yang, Kaiwei Liu, Muyun Mou, Peng Cui:
Emergence and Causality in Complex Systems: A Survey on Causal Emergence and Related Quantitative Studies. CoRR abs/2312.16815 (2023) - 2022
- [i56]Xiangmeng Wang, Qian Li, Dianer Yu, Peng Cui, Zhichao Wang, Guandong Xu:
Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation. CoRR abs/2202.02576 (2022) - [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
- [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
- [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) - 2019
- [i18]Shengze Yu, Xin Wang, Wenwu Zhu, Peng Cui, Jingdong Wang:
Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation. CoRR abs/1901.00171 (2019) - [i17]Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, Philip S. Yu, Yanfang Ye:
Heterogeneous Graph Attention Network. CoRR abs/1903.07293 (2019) - [i16]Yue He, Zheyan Shen, Peng Cui:
NICO: A Dataset Towards Non-I.I.D. Image Classification. CoRR abs/1906.02899 (2019) - [i15]Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang:
The General Black-box Attack Method for Graph Neural Networks. CoRR abs/1908.01297 (2019) - [i14]Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang, Wenwu Zhu:
Learning Disentangled Representations for Recommendation. CoRR abs/1910.14238 (2019) - [i13]Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, Xiaowei Zhang:
Rule-Guided Compositional Representation Learning on Knowledge Graphs. CoRR abs/1911.08935 (2019) - [i12]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. CoRR abs/1911.12580 (2019) - 2018
- [i11]Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, Wenwu Zhu:
Billion-scale Network Embedding with Iterative Random Projection. CoRR abs/1805.02396 (2018) - [i10]Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li:
Stable Prediction across Unknown Environments. CoRR abs/1806.06270 (2018) - [i9]Yadan Luo, Yang Li, Fumin Shen, Yang Yang, Peng Cui, Zi Huang:
Collaborative Learning for Extremely Low Bit Asymmetric Hashing. CoRR abs/1809.09329 (2018) - [i8]Ziwei Zhang, Peng Cui, Wenwu Zhu:
Deep Learning on Graphs: A Survey. CoRR abs/1812.04202 (2018) - 2017
- [i7]Chengxi Zang, Peng Cui, Chaoming Song, Christos Faloutsos, Wenwu Zhu:
Structural patterns of information cascades and their implications for dynamics and semantics. CoRR abs/1708.02377 (2017) - [i6]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li:
On Image Classification: Correlation v.s. Causality. CoRR abs/1708.06656 (2017) - [i5]Linjun Zhou, Peng Cui, Shiqiang Yang, Wenwu Zhu, Qi Tian:
Learning to Learn Image Classifiers with Informative Visual Analogy. CoRR abs/1710.06177 (2017) - [i4]Peng Cui, Xiao Wang, Jian Pei, Wenwu Zhu:
A Survey on Network Embedding. CoRR abs/1711.08752 (2017) - [i3]Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu:
TIMERS: Error-Bounded SVD Restart on Dynamic Networks. CoRR abs/1711.09541 (2017) - [i2]Ke Tu, Peng Cui, Xiao Wang, Fei Wang, Wenwu Zhu:
Structural Deep Embedding for Hyper-Networks. CoRR abs/1711.10146 (2017) - 2015
- [i1]Linyun Yu, Peng Cui, Fei Wang, Chaoming Song, Shiqiang Yang:
From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics. CoRR abs/1505.07193 (2015)
Coauthor Index
Shiqiang Yang
aka: Shi-Qiang Yang
aka: Shi-Qiang Yang
[j50] [j44] [j36] [j32] [j27] [j25] [j20] [j19] [j18] [j16] [j14] [j13] [j12] [j10] [j9] [j8] [j7] [j6] [j5] [j4] [j3] [j2] [j1] [c139] [c104] [c91] [c66] [c65] [c55] [c54] [c53] [c51] [c48] [c47] [c44] [c38] [c37] [c34] [c32] [c31] [c30] [c29] [c27] [c24] [c22] [c21] [c20] [c19] [c17] [c16] [c14] [c13] [c12] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1] [p1] [i27] [i21] [i5] [i1]
[j57] [j56] [j55] [j46] [j43] [j37] [j35] [j33] [j31] [j30] [j29] [j28] [j25] [j21] [j17] [j16] [j15] [j14] [j13] [j10] [j9] [j8] [j7] [c152] [c142] [c133] [c123] [c121] [c118] [c115] [c109] [c101] [c91] [c86] [c85] [c83] [c82] [c81] [c79] [c78] [c76] [c75] [c74] [c72] [c71] [c70] [c69] [c68] [c67] [c63] [c62] [c61] [c60] [c59] [c54] [c52] [c50] [c49] [c46] [c45] [c44] [c42] [c40] [c36] [c35] [c34] [c32] [c30] [c29] [c27] [c20] [c19] [c17] [c16] [c14] [c13] [c12] [p1] [e2] [i41] [i35] [i32] [i31] [i26] [i20] [i18] [i15] [i14] [i11] [i8] [i7] [i5] [i4] [i3] [i2]
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