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ORCIDPhilip S. Yu
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- affiliation: University of Illinois at Chicago, Department of Computer Science, Chicago, IL, USA
- affiliation (PhD): Stanford University, Stanford, CA, USA
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2020 – today
- 2023
[j513]Shuai Zhou
, Chi Liu, Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Adversarial Attacks and Defenses in Deep Learning: From a Perspective of Cybersecurity. ACM Comput. Surv. 55(8): 163:1-163:39 (2023)- [j512]Guiling Li, Shaolin Xu, Senzhang Wang, Philip S. Yu:
Forest based on Interval Transformation (FIT): A time series classifier with adaptive features. Expert Syst. Appl. 213(Part C): 118923 (2023) - [j511]Chuanren Liu, Ehsan Fakharizadi, Tong Xu, Philip S. Yu:
Recent advances in domain-driven data mining. Int. J. Data Sci. Anal. 15(1): 1-7 (2023) - [j510]Zhimeng Yang, Yazhou Ren, Zirui Wu, Ming Zeng, Jie Xu, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
DC-FUDA: Improving deep clustering via fully unsupervised domain adaptation. Neurocomputing 526: 109-120 (2023) - [j509]Junsan Zhang, Xiaomin Wang, Yao Wan, Leiquan Wang, Jian Wang, Philip S. Yu:
SOR-TC: Self-attentive octave ResNet with temporal consistency for compressed video action recognition. Neurocomputing 533: 191-205 (2023) - [j508]Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu, Weiping Ding:
Internet of Behaviors: A Survey. IEEE Internet Things J. 10(13): 11117-11134 (2023) - [j507]Yao Chen, Wensheng Gan, Yongdong Wu, Philip S. Yu:
Privacy-preserving federated mining of frequent itemsets. Inf. Sci. 625: 504-520 (2023) - [j506]Tao Zhang, Tianqing Zhu, Mengde Han, Fengwen Chen, Jing Li, Wanlei Zhou, Philip S. Yu:
Fairness in graph-based semi-supervised learning. Knowl. Inf. Syst. 65(2): 543-570 (2023) - [j505]Xingcheng Fu, Jianxin Li, Jia Wu, Jiawen Qin, Qingyun Sun, Cheng Ji, Senzhang Wang, Hao Peng, Philip S. Yu:
Adaptive curvature exploration geometric graph neural network. Knowl. Inf. Syst. 65(5): 2281-2304 (2023) - [j504]Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
CIFair: Constructing continuous domains of invariant features for image fair classifications. Knowl. Based Syst. 268: 110417 (2023) - [j503]Tao Zhang, Tianqing Zhu, Jing Li, Wanlei Zhou, Philip S. Yu:
Revisiting model fairness via adversarial examples. Knowl. Based Syst. 277: 110777 (2023) - [j502]Hao Peng, Ruitong Zhang, Shaoning Li, Yuwei Cao, Shirui Pan, Philip S. Yu:
Reinforced, Incremental and Cross-Lingual Event Detection From Social Messages. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 980-998 (2023) - [j501]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2208-2225 (2023) - [j500]Jianxin Li, Qingyun Sun, Hao Peng, Beining Yang, Jia Wu, Philip S. Yu:
Adaptive Subgraph Neural Network With Reinforced Critical Structure Mining. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8063-8080 (2023) - [j499]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu:
Discovering High Utility Episodes in Sequences. IEEE Trans. Artif. Intell. 4(3): 473-486 (2023) - [j498]Tao Zhang, Congying Xia, Zhiwei Liu, Shu Zhao, Hao Peng, Philip S. Yu:
Domain-Invariant Feature Progressive Distillation with Adversarial Adaptive Augmentation for Low-Resource Cross-Domain NER. ACM Trans. Asian Low Resour. Lang. Inf. Process. 22(3): 76:1-76:21 (2023) - [j497]Shuang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu:
A Multi-Level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference. IEEE ACM Trans. Audio Speech Lang. Process. 31: 1771-1783 (2023) - [j496]Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. IEEE Trans. Big Data 9(2): 415-436 (2023) - [j495]Chunkai Zhang, Quanjian Dai, Zilin Du, Wensheng Gan, Jian Weng, Philip S. Yu:
TUSQ: Targeted High-Utility Sequence Querying. IEEE Trans. Big Data 9(2): 512-527 (2023) - [j494]Xuan Lin, Zhe Quan, Zhi-Jie Wang, Yan Guo, Xiangxiang Zeng, Philip S. Yu:
Effectively Identifying Compound-Protein Interaction Using Graph Neural Representation. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 932-943 (2023) - [j493]Yan Kang, Haining Wang, Bin Pu, Liu Tao, Jianguo Chen, Philip S. Yu:
A Hybrid Two-Stage Teaching-Learning-Based Optimization Algorithm for Feature Selection in Bioinformatics. IEEE ACM Trans. Comput. Biol. Bioinform. 20(3): 1746-1760 (2023) - [j492]Tingting Liang, Congying Xia, Ziqiang Zhao, Yixuan Jiang, Yuyu Yin, Philip S. Yu:
Transferring From Textual Entailment to Biomedical Named Entity Recognition. IEEE ACM Trans. Comput. Biol. Bioinform. 20(4): 2577-2586 (2023) - [j491]Ling Huang, Chang-Dong Wang, Philip S. Yu:
Higher Order Connection Enhanced Community Detection in Adversarial Multiview Networks. IEEE Trans. Cybern. 53(5): 3060-3074 (2023) - [j490]Gengsen Huang, Wensheng Gan, Jian Weng, Philip S. Yu:
US-Rule: Discovering Utility-driven Sequential Rules. ACM Trans. Knowl. Discov. Data 17(1): 10:1-10:22 (2023) - [j489]Jie Yang, Zhixiao Wang, Xiaobin Rui, Yahui Chai, Philip S. Yu, Lichao Sun:
Triadic Closure Sensitive Influence Maximization. ACM Trans. Knowl. Discov. Data 17(6): 77:1-77:26 (2023) - [j488]Houye Ji, Xiao Wang, Chuan Shi, Bai Wang, Philip S. Yu:
Heterogeneous Graph Propagation Network. IEEE Trans. Knowl. Data Eng. 35(1): 521-532 (2023) - [j487]Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip S. Yu, Lifang He:
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(1): 560-574 (2023) - [j486]Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip S. Yu, Weixiong Zhang:
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. IEEE Trans. Knowl. Data Eng. 35(2): 1149-1170 (2023) - [j485]Dongxiao He, Tao Wang, Lu Zhai, Di Jin, Liang Yang, Yuxiao Huang, Zhiyong Feng, Philip S. Yu:
Adversarial Representation Mechanism Learning for Network Embedding. IEEE Trans. Knowl. Data Eng. 35(2): 1200-1213 (2023) - [j484]Qiaomin Yi, Ning Yang, Philip S. Yu:
Dual Adversarial Variational Embedding for Robust Recommendation. IEEE Trans. Knowl. Data Eng. 35(2): 1421-1433 (2023) - [j483]Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Learning Graph Convolutional Networks Based on Quantum Vertex Information Propagation. IEEE Trans. Knowl. Data Eng. 35(2): 1747-1760 (2023) - [j482]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2641-2656 (2023) - [j481]Hao Peng, Jianxin Li, Zheng Wang, Renyu Yang, Mingsheng Liu, Mingming Zhang, Philip S. Yu, Lifang He:
Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. IEEE Trans. Knowl. Data Eng. 35(3): 2765-2780 (2023) - [j480]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu:
Signed Network Representation by Preserving Multi-Order Signed Proximity. IEEE Trans. Knowl. Data Eng. 35(3): 3087-3100 (2023) - [j479]Zhenyu Qiu, Jia Wu, Wenbin Hu, Bo Du, Guocai Yuan, Philip S. Yu:
Temporal Link Prediction With Motifs for Social Networks. IEEE Trans. Knowl. Data Eng. 35(3): 3145-3158 (2023) - [j478]Lefeng Zhang, Tianqing Zhu, Ping Xiong, Wanlei Zhou, Philip S. Yu:
A Robust Game-Theoretical Federated Learning Framework With Joint Differential Privacy. IEEE Trans. Knowl. Data Eng. 35(4): 3333-3346 (2023) - [j477]Di Jin, Zhizhi Yu, Dongxiao He, Carl Yang, Philip S. Yu, Jiawei Han:
GCN for HIN via Implicit Utilization of Attention and Meta-Paths. IEEE Trans. Knowl. Data Eng. 35(4): 3925-3937 (2023) - [j476]Xusheng Zhao, Qiong Dai, Jia Wu, Hao Peng, Mingsheng Liu, Xu Bai, Jianlong Tan, Senzhang Wang, Philip S. Yu:
Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation. IEEE Trans. Knowl. Data Eng. 35(4): 4077-4091 (2023) - [j475]Xiaoming Liu, Zhanwei Zhang, Lingjuan Lyu, Zhaohan Zhang, Shuai Xiao, Chao Shen, Philip S. Yu:
Traffic Anomaly Prediction Based on Joint Static-Dynamic Spatio-Temporal Evolutionary Learning. IEEE Trans. Knowl. Data Eng. 35(5): 5356-5370 (2023) - [j474]Li Sun, Zhongbao Zhang, Feiyang Wang, Pengxin Ji, Jian Wen, Sen Su, Philip S. Yu:
Aligning Dynamic Social Networks: An Optimization Over Dynamic Graph Autoencoder. IEEE Trans. Knowl. Data Eng. 35(6): 5597-5611 (2023) - [j473]Jiyue Li, Senzhang Wang, Jiaqiang Zhang, Hao Miao, Junbo Zhang, Philip S. Yu:
Fine-Grained Urban Flow Inference With Incomplete Data. IEEE Trans. Knowl. Data Eng. 35(6): 5851-5864 (2023) - [j472]Yixin Liu, Ming Jin, Shirui Pan, Chuan Zhou, Yu Zheng, Feng Xia, Philip S. Yu:
Graph Self-Supervised Learning: A Survey. IEEE Trans. Knowl. Data Eng. 35(6): 5879-5900 (2023) - [j471]Gaoyang Guo, Chaokun Wang, Bencheng Yan, Yunkai Lou, Hao Feng, Junchao Zhu, Jun Chen, Fei He, Philip S. Yu:
Learning Adaptive Node Embeddings Across Graphs. IEEE Trans. Knowl. Data Eng. 35(6): 6028-6042 (2023) - [j470]Tengfei Ma, Xuan Lin, Bosheng Song, Philip S. Yu, Xiangxiang Zeng:
KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction. IEEE Trans. Knowl. Data Eng. 35(7): 7068-7081 (2023) - [j469]Daokun Zhang, Jie Yin, Philip S. Yu:
Link Prediction with Contextualized Self-Supervision. IEEE Trans. Knowl. Data Eng. 35(7): 7138-7151 (2023) - [j468]Jie Xu, Yazhou Ren, Huayi Tang, Zhimeng Yang, Lili Pan, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7470-7482 (2023) - [j467]Lichao Sun, Yingtong Dou, Carl Yang, Kai Zhang, Ji Wang, Philip S. Yu, Lifang He, Bo Li:
Adversarial Attack and Defense on Graph Data: A Survey. IEEE Trans. Knowl. Data Eng. 35(8): 7693-7711 (2023) - [j466]Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, Philip S. Yu:
Generalizing to Unseen Domains: A Survey on Domain Generalization. IEEE Trans. Knowl. Data Eng. 35(8): 8052-8072 (2023) - [j465]Tingting Liang, Congying Xia, Haoran Xu, Ziqiang Zhao, Yuyu Yin, Liang Chen, Philip S. Yu:
Modeling Reviews for Few-Shot Recommendation via Enhanced Prototypical Network. IEEE Trans. Knowl. Data Eng. 35(9): 9407-9420 (2023) - [j464]Yang Gao, Peng Zhang, Chuan Zhou, Hong Yang, Zhao Li, Yue Hu, Philip S. Yu:
HGNAS++: Efficient Architecture Search for Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(9): 9448-9461 (2023) - [j463]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Multiview Clustering via Proximity Learning in Latent Representation Space. IEEE Trans. Neural Networks Learn. Syst. 34(2): 973-986 (2023) - [j462]Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Shan Xue, Qianli Xing, Philip S. Yu:
C-DeepTrust: A Context-Aware Deep Trust Prediction Model in Online Social Networks. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2767-2780 (2023) - [j461]Tao Zhang, Tianqing Zhu, Kun Gao, Wanlei Zhou, Philip S. Yu:
Balancing Learning Model Privacy, Fairness, and Accuracy With Early Stopping Criteria. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5557-5569 (2023) - [j460]Yiqi Wang, Chaozhuo Li, Zheng Liu, Mingzheng Li, Jiliang Tang, Xing Xie, Lei Chen, Philip S. Yu:
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering. ACM Trans. Inf. Syst. 41(2): 43:1-43:27 (2023) - [j459]Tianqing Zhu, Dayong Ye, Zishuo Cheng, Wanlei Zhou, Philip S. Yu:
Learning Games for Defending Advanced Persistent Threats in Cyber Systems. IEEE Trans. Syst. Man Cybern. Syst. 53(4): 2410-2422 (2023) - [c1016]Li Sun, Junda Ye, Hao Peng, Feiyang Wang, Philip S. Yu:
Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces. AAAI 2023: 4633-4642 - [c1015]Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu:
Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information. AAAI 2023: 4643-4651 - [c1014]Jiangshu Du, Wenpeng Yin, Congying Xia, Philip S. Yu:
Learning to Select from Multiple Options. AAAI 2023: 12754-12762 - [c1013]Xuming Hu, Zhijiang Guo, Zhiyang Teng, Irwin King, Philip S. Yu:
Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesis. ACL (2) 2023: 303-311 - [c1012]Fukun Ma, Xuming Hu, Aiwei Liu, Yawen Yang, Shuang Li, Philip S. Yu, Lijie Wen:
AMR-based Network for Aspect-based Sentiment Analysis. ACL (1) 2023: 322-337 - [c1011]Shuang Li, Xuming Hu, Aiwei Liu, Yawen Yang, Fukun Ma, Philip S. Yu, Lijie Wen:
Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizer. ACL (Findings) 2023: 1361-1374 - [c1010]Xuming Hu, Shen Wang, Xiao Qin, Chuan Lei, Zhengyuan Shen, Christos Faloutsos, Asterios Katsifodimos, George Karypis, Lijie Wen, Philip S. Yu:
Automatic Table Union Search with Tabular Representation Learning. ACL (Findings) 2023: 3786-3800 - [c1009]Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang, Pengjun Xie, Fei Huang, Lijie Wen, Philip S. Yu:
Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks. ACL (Findings) 2023: 9072-9087 - [c1008]Hoang Nguyen, Chenwei Zhang, Tao Zhang, Eugene Rohrbaugh, Philip S. Yu:
Enhancing Cross-lingual Transfer via Phonemic Transcription Integration. ACL (Findings) 2023: 9163-9175 - [c1007]Xuming Hu, Aiwei Liu, Zeqi Tan, Xin Zhang, Chenwei Zhang, Irwin King, Philip S. Yu:
GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks. ACL (Findings) 2023: 10221-10234 - [c1006]Mingxia Wang, Yun Xiong, Yao Zhang, Philip S. Yu, Yangyong Zhu:
Hierarchical Encoder-Decoder with Addressable Memory Network for Diagnosis Prediction. DASFAA (4) 2023: 266-275 - [c1005]Yahui Chai, Xiaobin Rui, Jie Yang, Philip S. Yu, Zhixiao Wang:
A Graph Embedding Approach for Link Prediction via Triadic Closure Based Direct Aggregation and Weighted Concatenation. DASFAA (3) 2023: 341-350 - [c1004]Chin-Yuan Yeh, Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
Planning Data Poisoning Attacks on Heterogeneous Recommender Systems in a Multiplayer Setting. ICDE 2023: 2510-2523 - [c1003]Li Sun, Feiyang Wang, Junda Ye, Hao Peng, Philip S. Yu:
CONGREGATE: Contrastive Graph Clustering in Curvature Spaces. IJCAI 2023: 2296-2305 - [c1002]Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu:
Hierarchical State Abstraction based on Structural Information Principles. IJCAI 2023: 4549-4557 - [c1001]Yuefei Lyu, Xiaoyu Yang, Jiaxin Liu, Sihong Xie, Philip S. Yu, Xi Zhang:
Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection. IJCNN 2023: 1-9 - [c1000]Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. KDD 2023: 93-104 - [c999]Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Cheng, Bing Yin, Suhang Wang, Philip S. Yu:
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD 2023: 5162-5173 - [c998]Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson:
The 12th International Workshop on Urban Computing. KDD 2023: 5874-5875 - [c997]Yuwei Cao, Liangwei Yang, Chen Wang, Zhiwei Liu, Hao Peng, Chenyu You, Philip S. Yu:
Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation. RecSys 2023: 322-333 - [c996]Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen Guo, Philip S. Yu:
Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce. SIGIR 2023: 1884-1888 - [c995]Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu:
Graph Collaborative Signals Denoising and Augmentation for Recommendation. SIGIR 2023: 2037-2041 - [c994]Xuming Hu, Zhaochen Hong, Zhijiang Guo, Lijie Wen, Philip S. Yu:
Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence. SIGIR 2023: 2319-2323 - [c993]Xuming Hu, Junzhe Chen, Shiao Meng, Lijie Wen, Philip S. Yu:
SelfLRE: Self-refining Representation Learning for Low-resource Relation Extraction. SIGIR 2023: 2364-2368 - [c992]Xuming Hu, Zhaochen Hong, Chenwei Zhang, Irwin King, Philip S. Yu:
Think Rationally about What You See: Continuous Rationale Extraction for Relation Extraction. SIGIR 2023: 2436-2440 - [c991]Xuming Hu, Zhijiang Guo, Junzhe Chen, Lijie Wen, Philip S. Yu:
MR2: A Benchmark for Multimodal Retrieval-Augmented Rumor Detection in Social Media. SIGIR 2023: 2901-2912 - [c990]Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang:
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation. WSDM 2023: 661-669 - [c989]Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu:
Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph. WSDM 2023: 769-777 - [c988]Xiaosu Wang, Yun Xiong, Beichen Kang, Yao Zhang, Philip S. Yu, Yangyong Zhu:
Reducing Negative Effects of the Biases of Language Models in Zero-Shot Setting. WSDM 2023: 904-912 - [c987]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. WSDM 2023: 922-930 - [c986]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, Philip S. Yu:
ConsRec: Learning Consensus Behind Interactions for Group Recommendation. WWW 2023: 240-250 - [c985]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. WWW 2023: 251-262 - [c984]Dongcheng Zou, Hao Peng, Xiang Huang, Renyu Yang, Jianxin Li, Jia Wu, Chunyang Liu, Philip S. Yu:
SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization. WWW 2023: 499-510 - [c983]Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ming-Syan Chen:
CMINet: a Graph Learning Framework for Content-aware Multi-channel Influence Diffusion. WWW 2023: 545-555 - [c982]Wensheng Gan, Zhenqiang Ye, Shicheng Wan, Philip S. Yu:
Web 3.0: The Future of Internet. WWW (Companion Volume) 2023: 1266-1275 - [c981]Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu:
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation. WWW 2023: 1375-1385 - [c980]Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. WWW 2023: 3978-3986 - [c979]Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu:
Graph-based Village Level Poverty Identification. WWW 2023: 4115-4119 - [i411]Qingyun Sun, Jianxin Li, Beining Yang, Xingcheng Fu, Hao Peng, Philip S. Yu:
Self-organization Preserved Graph Structure Learning with Principle of Relevant Information. CoRR abs/2301.00015 (2023) - [i410]Xiaohan Li, Yuqing Liu, Zheng Liu, Philip S. Yu:
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. CoRR abs/2301.03780 (2023) - [i409]Lilin Zhang, Ning Yang, Yanchao Sun, Philip S. Yu:
Provable Unrestricted Adversarial Training without Compromise with Generalizability. CoRR abs/2301.09069 (2023) - [i408]Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu:
Unbiased and Efficient Self-Supervised Incremental Contrastive Learning. CoRR abs/2301.12104 (2023) - [i407]Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu:
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation. CoRR abs/2301.12197 (2023) - [i406]Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu:
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization. CoRR abs/2302.00109 (2023) - [i405]Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, Philip S. Yu:
ConsRec: Learning Consensus Behind Interactions for Group Recommendation. CoRR abs/2302.03555 (2023) - [i404]Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao:
Weakly Supervised Anomaly Detection: A Survey. CoRR abs/2302.04549 (2023) - [i403]Jing Ma, Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu:
Graph-based Village Level Poverty Identification. CoRR abs/2302.06862 (2023) - [i402]Haoran Wang, Yingtong Dou, Canyu Chen, Lichao Sun, Philip S. Yu, Kai Shu:
Attacking Fake News Detectors via Manipulating News Social Engagement. CoRR abs/2302.07363 (2023) - [i401]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. CoRR abs/2302.09419 (2023) - [i400]