[The Web Conference 2023]
Graph-based Village Level Poverty Identification. Liangwei Yang, Qiong Feng, Weizhi Zhang, Philip S. Yu. [Code]
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation . Ziwei Fan, Zhiwei Liu, Hao Peng, Philip S. Yu. [Code]
[SIGIR 2023]
Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce. Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen Guo, Philip S. Yu.
Graph Collaborative Signals Denoising and Augmentation for Recommendation. Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu. [Code]
[TALLIP 2022]
Domain-Invariant Feature Progressive Distillation with Adversarial Adaptive Augmentation for Low-Resource Cross-Domain NER. Tao Zhang, Congying Xia, Zhiwei Liu, Shu Zhao, Hao Peng, Philip S. Yu.
[BigData 2022]
MetaKRec: Collaborative Meta-Knowledge Enhanced Recommender System. Liangwei Yang, Shen Wang, Jibing Gong, Shaojie Zheng, Shuying Du, Zhiwei Liu, Philip S. Yu. [Code]
Continuous Prompt Tuning Based Textual Entailment Model for E-commerce Entity Typing. Yibo Wang, Congying Xia, Guan Wang, and Philip S. Yu. [Code]
Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer. Ziwei Fan, Zhiwei Liu, Chen Wang, Peijie Huang, Hao Peng, Philip S. Yu. [Code]
Time-aware Hyperbolic Graph Attention Network for Session-based Recommendation. Xiaohan Li*, Yuqing Liu*, Zheng Liu, Philip S. Yu.
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders. Xiaohan Li*, Zheng Liu*, Luyi Ma, Kaushiki Nag, Stephen Guo, Philip Yu, Kannan Achan.
[CIKM 2022]
ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation. Yu Wang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, Philip S Yu. [Code]
[WSDM 2022]
Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph. Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu.
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation. Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang. [Code]
[NeurIPS 2022]
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H Chen, Zhihao Jia, Philip S Yu. [Code]
[The Web Conference 2022]
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu. [Code]
Sequential recommendation via stochastic self-attention. Ziwei Fan, Zhiwei Liu, Alice Wang, Zahra Nazari, Lei Zheng, Peng Hao, and Philip S Yu. [Code]
[TIST 2021]
Federated Social Recommendation with Graph Neural Network. Zhiwei Liu, Liangwei Yang, Ziwei Fan, Hao Peng, Philip S. Yu.
[TKDE]
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip Yu, Lifang He. [Code]
[TPAMI]
Reinforced, Incremental and Cross-lingual Event Detection From Social Messages. Hao Peng, Ruitong Zhang, Shaoning Li, Yuwei Cao, Shirui Pan, Philip Yu. [Code]
[EMNLP 2021]
PDALN: Progressive Domain Adaptation over a Pre-trained Model for Low-Resource Cross-Domain Named Entity Recognition. Tao Zhang, Congying Xia, Philip S. Yu, Zhiwei Liu, Shu Zhao.
[CogMI 2021]
Pre-training Graph Neural Network for Cross Domain Recommendation. Chen Wang, Yueqing Liang, Zhiwei Liu, Tao Zhang.
[BigData 2021]
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network. Xiaohan Li, Zhiwei Liu, Stephen Guo, Zheng Liu, Hao Peng, Philip S. Yu, Kannan Achan.
Deep Fraud Detection on Non-attributed Graph. Chen Wang, Yingtong Dou, Min Chen, Jia Chen, Zhiwei Liu, Philip S. Yu.
[NeurIPS 2021]
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip Yu. [Code]
[CIKM 2021]
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN. Yu Wang, Zhiwei Liu, Ziwei Fan, Lichao Sun, Philip Yu. [Code]
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer. Ziwei Fan*, Zhiwei Liu*, Jiawei Zhang, Yun Xiong, Lei Zheng, and Philip S. Yu (* is equal contribution). [Code]
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation. Ziwei Fan, Zhiwei Liu, Lei Zheng, Shen Wang, Philip S. Yu. [Code]
[SIGIR 2021]
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. Zheng Liu*, Xiaohan Li*, Zeyu You, Tao Yang, Wei Fan and Philip Yu. (* indicates equal contribution.)
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. Zhiwei Liu*, Ziwei Fan*, Yu Wang and Philip S. Yu. (* indicates equal contribution.) [Code]
ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu.
User Preference-aware Fake News Detection. Yingtong Dou, Kai Shu, Congying Xia, Philip Yu and Lichao Sun. [Code]
Pseudo Siamese Network for Few-shot Intent Generation. Congying Xia, Caiming Xiong and Philip Yu.
[NAACL 2021]
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li and Philip Yu.
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. Congying Xia*, Wenpeng Yin*, Yihao Feng, Philip Yu. (* indicates equal contribution.)
[The Web Conference 2021]
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu. [Code]
Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion. Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew Arnold, Bing Xiang, Philip S. Yu, Isabel F. Cruz.
[AAAI 2021]
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning, Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S Yu. [Code]
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs. Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu.
[EACL 2021]
Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation, Ye Liu, Yao Wan, Jianguo Zhang, Wenting Zhao, Philip S Yu.
[BIGDATA 2020]
Basket Recommendation with Multi-Intent Translation Graph Neural Network. Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu. [Code]
Heterogeneous Similarity Graph Neural Network on Electronic Health Record. Zheng Liu, Xiaohan Li, Lifang He, Hao Peng, and Philip Yu.
[COLING 2020]
Memory Augmented Zero-Shot Fine-grained Named Entity Typing. Tao Zhang, Congying Xia, Chun-Ta Lu and Philip Yu.
Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation. Zhongfen Deng, Hao Peng, Congying Xia, Jianxin Li, Lifang He and Philip Yu.
Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks. Lichao Sun*, Congying Xia*, Wenpeng Yin, Tingting Liang, Philip Yu and Lifang He. (* indicates equal contribution.)
[SEM 2020]
Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking. Jianguo Zhang , Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S Yu, Richard Socher, Caiming Xiong.
Improving Medical NLI Using Context-Aware Domain Knowledge. Shaika Chowdhury, Philip S. Yu and Yuan Luo
[EMNLP 2020]
Discriminative Nearest Neighbor Few-shot Intent Detection by Transfering Natural Language Inference. Jianguo Zhang, Kazuma Hashimoto, Wenhao Liu, Chien-Sheng Wu, Yao Wan, Philip S. Yu, Richard Socher and Caiming Xiong. EMNLP 2020.
Composed Variational Natural Language Generation for Few-shot Intents. Congying Xia, Caiming Xiong, Philip S. Yu, Richard Socher. Findings of EMNLP 2020.
Semantic Matching and Aggregation Network for Few-shot Intent Detection. Hoang Nguyen, Chenwei Zhang, Congying Xia, Philip S. Yu. Findings of EMNLP 2020.
[ACCV 2020]
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score. He Huang, Shunta Saito, Yuta Kikuchi, Eiichi Matsumoto, Wei Tang, Philip S Yu.
[BMVC 2020]
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge. He Huang, Yuanwei Chen, Wei Tang, Wenhao Zheng, Qing-Guo Chen, Philip Yu. (Oral)
[ICDM 2020]
Dynamic Graph Collaborative Filtering. Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, and Philip S. Yu.
PERFECT: A Hyperbolic Embedding for Joint Social Network Alignment. Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Yang Du, Sen Su, and Philip S. Yu.
[CIKM 2020]
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters. Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu. [Code]
[SIGDIAL 2020]
Commonsense Evidence Generation and Injection in Reading Comprehension. Ye Liu, Tao Yang, Zeyu You, Wei Fan and Philip S. Yu.
[IJCAI 2020]
Entity Synonym Discovery via Multi-piece Bilateral Context Matching. Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu. [Code]
[KDD 2020]
Robust Spammer Detection by Nash Reinforcement Learning. Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie. [code]
[SIGIR 2020]
Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection. Zhiwei Liu, Yingtong Dou, Yutong Deng, Hao Peng and Philip S. Yu. [code]
Joint Training Capsule Network for Cold Start Recommendation. Tingting Liang, Congying Xia, Yuyu Yin and Philip Yu.
[PAKDD 2020]
Multi-information Source HIN for Medical Concept Embedding. Yuwei Cao, Hao Peng and Philip S. Yu.
[SDM 2020]
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network. Zhiwei Liu, Mengting Wan, Stephen Guo, Kannan Achan, Philip S Yu. [code]
[CIKM 2019]
Generative Question Refinement with Deep ReinforcementLearning in Retrieval-based QA System. Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S.Yu
Multi-Hot Compact Network Embedding. Chaozhuo Li, Lei Zheng, Senzhang Wang, Feiran Huang, Philip S. Yu, Zhoujun Li
Video-level Multi-model fusion for action recognition. Xiaomin Wang, Junsan Zhang, Leiquan Wang, Philip S. Yu, Jie Zhu, Haisheng Li
Partially Shared Adversarial Learning For Semi-supervised Multi-platform User Identity Linkage. Chaozhuo Li, Senzhang Wang, Yanbo Liang, Philip S. Yu, Zhoujun Li
[ACL 2019]
Multi-grained Named Entity Recognition. Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip Yu. [code]
Joint Slot Filling and Intent Detection via Capsule Neural Networks. Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip Yu. [code]
[SIGIR 2019]
Deep Distribution Network: Addressing the Data Sparsity Issue for Top-N Recommendation. Lei Zheng, Chaozhuo Li, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu
Gated Spectral Units: Modeling Co-evolving Patterns for Sequential Recommendation. Lei Zheng, Ziwei Fan, Chun-Ta Lu, Jiawei Zhang, Philip S. Yu
[CVPR 2019]
Generative Dual Adversarial Network for Generalized Zero-shot Learning. He Huang, Changhu Wang, Philip S. Yu, Chang-Dong Wang. [code]
[NAACL-HLT 2019]
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce. Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Xiuming Pan, Yu Gong, Philip S. Yu
Joint Training for Review Reading Comprehension and Aspect-based Sentiment Analysis. Hu Xu, Bing Liu, Lei Shu, Philip Yu
[IJCAI 2019]
Heterogeneous Graph Matching Networks for Unknown Malware Detection. Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu
Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization. Mehrnaz Najafi, Lifang He, Philip S. Yu
[AAAI 2019]
Private Model Compression via Knowledge Distillation. Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu
Adversarial Learning forWeakly-Supervised Social Network Alignment. Chaozhuo Li, Senzhang Wang, Yukun Wang, Philip S. Yu, Yanbo Liang, Yun Liu, Zhoujun Li
[SDM 2019]
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification. Shen Wang, Zhengzhang Chen, Ding Li, Lv-An Tang, Jingchao Ni, Zhichun Li, Junghwan Rhee, Haifeng Chen, Philip S Yu
[RecSys 2018]
Spectral Collaborative Filtering. Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip Yu. [code]
[ICDM 2018]
A Self-Organizing Tensor Architecture for Multi-View Clustering. Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, and Fei Wang
dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction. He Huang, Bokai Cao, Philip S. Yu, Chang-Dong Wang, and Alex D. Leow.
FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation. Fei Jiang, Lei Zheng, Jin Xu, and Philip S. Yu
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. Jianguo Zhang*, Ji Wang*, Lifang He, Zhao Li, and Philip S. Yu
SSDMV: Semi-supervised Deep Social Spammer Detection by Multi-View Data Fusion. Chaozhuo Li, Senzhang Wang, Lifang He, Philip S. Yu, Yanbo Liang, Zhoujun Li
[CIKM 2018]
Distribution Distance Minimization for Unsupervised User Identity Linkage. Chaozhuo Li, Senzhang Wang, Philip S. Yu, Lei Zheng, Xiaoming Zhang, Zhoujun Li, Yanbo Liang
[EMNLP 2018]
Zero-shot User Intent Detection via Capsule Neural Networks. Congying Xia*, Chenwei Zhang*, Xiaohui Yan, Yi Chang, Philip S. Yu. (* indicates equal contribution)
[ACL 2018]
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction. Hu Xu, Bing Liu, Lei Shu, Philip S. Yu
[KDD 2018]
On the Generative Discovery of Structured Medical Knowledge, Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu
Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud, Ji Wang*, Jianguo Zhang*, Weidong Bao, Xiaomin Zhu, Bokai Cao, Philip S. Yu
Multi-Round Influence Maximization, Lichao Sun, Weiran Huang, Philip Yu, Wei Chen
[IJCAI 2018]
Lifelong Domain Word Embedding via Meta-Learning, Hu Xu, Bing Liu, Lei Shu, Philip Yu
[SDM 2018]
On Spectral Graph Embedding: a Non-backtracking Perspective and Graph Approximation, Fei Jiang, Lifang He, Yi Zheng, Enqiang Zhu, Jin Xu and Philip S. Yu.
[WWW 2018]
Multi-Task Pharmacovigilance Mining from Social Media Posts, Shaika Chowdhury, Chenwei Zhang and Philip S. Yu.
On Exploring Semantic Meanings of Links for Embedding Social Networks, Linchuan Xu, Xiaokai Wei, Jiannong Cao and Philip S. Yu.
Learning from Multi-View Multi-Way Data via Structural Factorization Machines, Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao and Philip S. Yu.
[AAAI 2018]
Dual Attention Network for Product Compatibility and Function Satisfiability Analysis, Hu Xu, Sihong Xie, Shu Lei and Philip S. Yu.
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis, Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin and Alex D. Leow.
[ICDM 2017]
MNE: Emerging Network Embedding with Aligned Autoencoder, Jiawei Zhang, Congying Xia, Chenwei Zhang, Limeng Cui, Yanjie Fu and Philip S. Yu.
HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks, Bokai Cao, Mia Mao, Siim Viidu and Philip S. Yu.
Collaborative Inference of Coexisting Information Diffusions, Yanchao Sun, Cong Qian, Ning Yang and Philip S. Yu.
Multi-view Graph Embedding with Hub Detection for Brain Network Analysis, Guixiang Ma, Chun-Ta Lu, Lifang He, Philip S. Yu and Ann B. Ragin.
A Broad Learning Approach for Context-Aware Mobile Application Recommendation, Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu and Jian Wu.
[CIKM 2017]
ECD: Enterprise Social Community Detection via Hierarchical Structure Fusion, Jiawei Zhang, Limeng Cui, Philip S. Yu, Yuanhua Lv and Yanjie Fu.
Multi-Source Collaborative Recommendation, Junxing Zhu, Jiawei Zhang, Lifang He, Quanyuan Wu, Bin Zhou, Chenwei Zhang and Philip S. Yu.
Unsupervised Feature Selection with Heterogeneous Side Information, Xiaokai Wei, Bokai Cao and Philip S. Yu.
Multi-view Clustering via Graph Embedding for Connectome Analysis, Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow and Ann B. Ragin.
Coupled Sparse Matrix Factorization for Response Time Prediction in Logistics Services, Yuqi Wang, Jiannong Cao, Lifang He, Wengen Li, Lichao Sun and Philip S. Yu.
[KDD 2017]
Structural Deep Brain Network Mining, Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu and Ann B. Ragin.
DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection, Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta, Olu Ajilore, Kelly Ryan and Alex D. Leow. [code]
[ICML 2017]
Kernalized Support Tensor Machines, Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, Linlin Shen, Philip S. Yu and Ann B. Ragin.
[CVPR 2017]
Multi-way Multi-level Kernel Modeling for Neuroimaging Classification, Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, Linlin Shen, Philip S. Yu and Ann B. Ragin.
[IJCAI 2017]
SEVEN: Deep Semi-supervised Verification Networks, Vahid Noroozi, Lei Zheng, Sara Bahaadini, Sihong Xie and Philip S. Yu.
[SDM 2017]
t-BNE: Tensor-based Brain Network Embedding, Bokai Cao, Lifang He, Xiaokai Wei, Mengqi Xing, Philip S. Yu, Heide Klumpp and Alex D. Leow. [code]
[ICDE 2017]
Link Prediction across Aligned Networks with Sparse Low Rank Matrix Estimation, Jiawei Zhang, Jianhui Chen, Shi Zhi, Yi Chang, Philip S. Yu and Jiawei Han.
Enterprise Social Community Detection, Jiawei Zhang, Philip S. Yu and Yuanhua Lv.
[WWW 2017]
Cross View Link Prediction by Learning Noise-resilient Representation Consensus, Xiaokai Wei, Linchuan Xu, Bokai Cao and Philip S. Yu.
[WSDM 2017]
Embedding of Embedding (EOE) : Embedding for Coupled Heterogeneous Networks, Linchuan Xu, Xiaokai Wei, Jiannong Cao and Philip S. Yu.
Enterprise Employee Training via Project Team Formation, Jiawei Zhang, Philip S. Yu and Yuanhua Lv.
Joint Deep Modeling of Users and Items Using Reviews for Recommendation, Lei Zheng, Vahid Noroozi and Philip S. Yu.
Link Prediction with Cardinality Constraint, Jiawei Zhang, Jianhui Chen, Junxing Zhu, Yi Chang and Philip S. Yu.
Multilinear Factorization Machines for Multi-Task Multi-View Learning, Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao and Philip S. Yu. [code]
[ICDM 2016]
Online Unsupervised Multi-view Feature Selection, Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei and Philip S. Yu.
[CIKM 2016]
Information Diffusion at Workplace, Jiawei Zhang, Philip S. Yu, Yuanhua Lv and Qianyi Zhan.
Multi-source Hierarchical Prediction Consolidation, Chenwei Zhang, Sihong Xie, Yaliang Li, Jing Gao, Wei Fan and Philip S. Yu.
Active Zero-shot Learning, Sihong Xie, Shaoxiong Wang and Philip S. Yu.
Efficient Hidden Trajectory Reconstruction from Sparse Data, Ning Yang and Philip S. Yu.
[ECML/PKDD 2016]
Enhancing Traffic Congestion Estimation with Social Media by Coupled Hidden Markov Model, Senzhang Wang, Fengxiang Li, Leon Stenneth and Philip S. Yu.
Multi-Graph Clustering based on Interior-Node Topology with Applications to Brain Networks, Guixiang Ma, Lifang He, Bokai Cao, Jiawei Zhang and Philip S. Yu.
Semi-supervised Tensor Factorization for Brain Network Analysis, Bokai Cao, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu and Alex D. Leow.
Trust Hole Identification in Signed Networks, Jiawei Zhang, Qianyi Zhan, Lifang He, Charu Aggarwal and Philip S. Yu.
[KDD 2016]
Joint Community and Structural Hole Spanner Detection via Harmonic Modularity, Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen and Philip S. Yu. [code]
[IJCAI 2016]
Item Recommendation for Emerging Online Businesses, Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He and Philip S. Yu.
Understanding Information Diffusion under Interactions, Yuan Su, Xi Zhang, Philip S. Yu, Wen Hua, Xiaofang Zhou and Binxing Fang.
[SDM 2016]
Identifying Connectivity Patterns for Brain Diseases Via Multi-Side-View Guided Deep Architectures, Jingyuan Zhang, Bokai Cao, Sihong Xie, Chun-Ta Lu, Philip S. Yu and Ann B. Ragin.
Effective Crowd Expertise Modeling Via Cross Domain Sparsity and Uncertainty Reduction, Sihong Xie, Qingbo Hu, Weixiang Shao, Jingyuan Zhang, Jing Gao, Wei Fan and Philip S. Yu.
Nonlinear Joint Unsupervised Feature Selection, Xiaokai Wei, Bokai Cao and Philip S. Yu.
Spatio-Temporal Tensor Analysis for Whole-Brain Fmri Classification, Guixiang Ma, Lifang He, Chun-Ta Lu, Philip S. Yu, Linlin Shen and Ann B. Ragin.
[WWW 2016]
Mining Online Social Data for Detecting Social Netowrk Mental Disorders, Hong-Han Shuai, Chih-Ya Shen, De-Nian Yang, Yi-Feng Lan, Wang-Chien Lee, Philip S. Yu and Ming-Syan Chen.
PCT: Partial Co-Alignment of Social Networks, Jiawei Zhang and Philip S. Yu.
HeteroSales: Utilizing Heterogeneous Social Networks to Identify the Next Enterprise Customer, Qingbo Hu, Sihong Xie, Jiawei Zhang, Qiang Zhu, Songtao Guo and Philip S. Yu.
Mining User Intentions from Medical Queries: A Neural Network Based Heterogeneous Jointly Modeling Approach, Chenwei Zhang, Wei Fan, Nan Du and Philip S. Yu.
[WSDM 2016]
Multi-view Machines, Bokai Cao, Hucheng Zhou, Guoqiang Li and Philip S. Yu.
[AAAI 2016]
Unsupervised Feature Selection on Networks: A Generative View, Xiaokai Wei, Bokai Cao and Philip S. Yu.
[ICDM 2015]
Multiple Anonymized Social Networks Alignment, Jiawei Zhang and Philip S. Yu.
Mining Brain Networks Using Multiple Side Views for Neurological Disorder Identification, Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu and Ann B. Ragin. [code]
Ensemble of Diverse Sparsifications for Link Prediction in Large-Scale Networks, Yi-Ling Chen, Ming-Syan Chen and Philip S. Yu.
[CIKM 2015]
Learning Entity Types from Query Logs via Graph-Based Modeling, Jingyuan Zhang, Luo Jie, Altaf Rahman, Sihong Xie, Yi Chang and Philip S. Yu.
Enterprise Social Link Recommendation, Jiawei Zhang, Yuanhua Lv and Philip S. Yu.
Forming Online Support Groups for Internet and Behavior Related Addictions, Chih-Ya Shen, Hong-Han Shuai, De-Nian Yang, Yi-Feng Lan, Wang-Chien Lee, Philip S. Yu and Ming-Syan Chen.
Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks, Chuan Shi, Zhiqiang Zhang, Ping Luo, Philip S. Yu, Yading Yue and Bin Wu.
[ECML/PKDD 2015]
Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2, 1 Regularization, Weixiang Shao, Lifang He and Philip S. Yu.
Discovering Audience Groups and Group-Specific Influencers, Shuyang Lin, Qingbo Hu, Jingyuan Zhang and Philip S. Yu.
[KDD 2015]
Organizational Chart Inference, Jiawei Zhang, Philip S. Yu and Yuanhua Lv.
[IJCAI 2015]
Integrated Anchor and Social Link Predictions across Social Networks, Jiawei Zhang and Philip S. Yu.
[SDM 2015]
Efficient Partial Order Preserving Unsupervised Feature Selection on Networks, Xiaokai Wei, Sihong Xie and Philip S. Yu.
Community Detection for Emerging Networks, Jiawei Zhang and Philip S. Yu.
Frameworks to Encode User Preferences for Inferring Topic-sensitive Information Networks, Qingbo Hu, Sihong Xie, Shuyang Lin, Wei Fan and Philip S. Yu.
OnlineCM: Real-time Consensus Classification with Missing Values, Bowen Dong, Sihong Xie, Jing Gao, Wei Fan and Philip S. Yu.
Predicting Neighbor Distribution in Heterogeneous Information Networks, Yuchi Ma, Ning Yang, Chuan Li, Lei Zhang and Philip S. Yu.
[AAAI 2015]
Burst Time Prediction in Cascades, Senzhang Wang, Zhao Yan, Xia Hu, Philip S. Yu and Zhoujun Li.