The one-against-all partition based binary tree support vector machine algorithms for multi-class classification. - Xiaowei Yang 003; Qiaozhen Yu; Lifang He 001; Tengjiao Guo (Neurocomputing, 2013)

An adaptive class pairwise dimensionality reduction algorithm. - Lifang He 001; Xiaowei Yang 003; Zhifeng Hao (Neural Comput. Appl., 2013)

A Linear Support Higher-Order Tensor Machine for Classification. - Zhifeng Hao; Lifang He 001; Bingqian Chen; Xiaowei Yang 003 (IEEE Trans. Image Process., 2013)

Tensor-Based Multi-view Feature Selection with Applications to Brain Diseases. - Bokai Cao; Lifang He 001; Xiangnan Kong; Philip S. Yu; Zhifeng Hao; Ann B. Ragin (ICDM, 2014)

Low-Density Cut Based Tree Decomposition for Large-Scale SVM Problems. - Lifang He 001; Hong-Han Shuai; Xiangnan Kong; Zhifeng Hao; Xiaowei Yang 003; Philip S. Yu (ICDM, 2014)

DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. - Lifang He 001; Xiangnan Kong; Philip S. Yu; Xiaowei Yang 003; Ann B. Ragin; Zhifeng Hao (SDM, 2014)

A GA-based feature selection and parameter optimization for linear support higher-order tensor machine. - Tengjiao Guo; Le Han; Lifang He 001; Xiaowei Yang 003 (Neurocomputing, 2014)

A robust least squares support vector machine for regression and classification with noise. - Xiaowei Yang 003; Liangjun Tan; Lifang He 001 (Neurocomputing, 2014)

The Unsupervised Hierarchical Convolutional Sparse Auto-Encoder for Neuroimaging Data Classification. - Xiaobing Han; Yanfei Zhong; Lifang He 001; Philip S. Yu; Liangpei Zhang 001 (BIH, 2015)

Citywide traffic congestion estimation with social media. - Senzhang Wang; Lifang He 001; Leon Stenneth; Philip S. Yu; Zhoujun Li 001 (SIGSPATIAL/GIS, 2015)

Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization. - Weixiang Shao; Lifang He 001; Philip S. Yu (PAKDD (2), 2015)

Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2, 1 Regularization. - Weixiang Shao; Lifang He 001; Philip S. Yu (ECML/PKDD (1), 2015)

A bilateral-truncated-loss based robust support vector machine for classification problems. - Xiaowei Yang 003; Le Han; Yan Li; Lifang He 001 (Soft Comput., 2015)

A Low-Rank Approximation-Based Transductive Support Tensor Machine for Semisupervised Classification. - Xiaolan Liu 003; Tengjiao Guo; Lifang He 001; Xiaowei Yang 003 (IEEE Trans. Image Process., 2015)

Online multi-view clustering with incomplete views. - Weixiang Shao; Lifang He 001; Chun-Ta Lu; Philip S. Yu (IEEE BigData, 2016)

Online Unsupervised Multi-view Feature Selection. - Weixiang Shao; Lifang He 001; Chun-Ta Lu; Xiaokai Wei; Philip S. Yu (ICDM, 2016)

Item Recommendation for Emerging Online Businesses. - Chun-Ta Lu; Sihong Xie; Weixiang Shao; Lifang He 001; Philip S. Yu (IJCAI, 2016)

Multi-source Multi-view Clustering via discrepancy penalty. - Weixiang Shao; Jiawei Zhang 001; Lifang He 001; Philip S. Yu (IJCNN, 2016)

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. - Lifang He 001; Chun-Ta Lu; Jiaqi Ma 001; Jianping Cao; Linlin Shen; Philip S. Yu (KDD, 2016)

Estimating Urban Traffic Congestions with Multi-sourced Data. - Senzhang Wang; Lifang He 001; Leon Stenneth; Philip S. Yu; Zhoujun Li 001; Zhiqiu Huang (MDM, 2016)

Multi-graph Clustering Based on Interior-Node Topology with Applications to Brain Networks. - Guixiang Ma; Lifang He 001; Bokai Cao; Jiawei Zhang 001; Philip S. Yu; Ann B. Ragin (ECML/PKDD (1), 2016)

Trust Hole Identification in Signed Networks. - Jiawei Zhang 001; Qianyi Zhan; Lifang He 001; Charu C. Aggarwal; Philip S. Yu (ECML/PKDD (1), 2016)

Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification. - Guixiang Ma; Lifang He 001; Chun-Ta Lu; Philip S. Yu; Linlin Shen; Ann B. Ragin (SDM, 2016)

Intrusive tumor growth inspired optimization algorithm for data clustering. - De-Yu Tang; Shoubin Dong; Lifang He 001; Yi Jiang (Neural Comput. Appl., 2016)

Error-robust multi-view clustering. - Mehrnaz Najafi; Lifang He 001; Philip S. Yu (IEEE BigData, 2017)

Contaminant removal for Android malware detection systems. - Lichao Sun 001; Xiaokai Wei; Jiawei Zhang 001; Lifang He 001; Philip S. Yu; Witawas Srisa-an (IEEE BigData, 2017)

Multi-view Clustering with Graph Embedding for Connectome Analysis. - Guixiang Ma; Lifang He 001; Chun-Ta Lu; Weixiang Shao; Philip S. Yu; Alex D. Leow; Ann B. Ragin (CIKM, 2017)

Coupled Sparse Matrix Factorization for Response Time Prediction in Logistics Services. - Yuqi Wang; Jiannong Cao 001; Lifang He 001; Wengen Li; Lichao Sun 001; Philip S. Yu (CIKM, 2017)

Broad Learning based Multi-Source Collaborative Recommendation. - Junxing Zhu; Jiawei Zhang 001; Lifang He 001; Quanyuan Wu; Bin Zhou 004; Chenwei Zhang; Philip S. Yu (CIKM, 2017)

Multi-way Multi-level Kernel Modeling for Neuroimaging Classification. - Lifang He 001; Chun-Ta Lu; Hao Ding 003; Shen Wang 005; Linlin Shen; Philip S. Yu; Ann B. Ragin (CVPR, 2017)

A Broad Learning Approach for Context-Aware Mobile Application Recommendation. - Tingting Liang; Lifang He 001; Chun-Ta Lu; Liang Chen 001; Philip S. Yu; Jian Wu 001 (ICDM, 2017)

Multi-view Graph Embedding with Hub Detection for Brain Network Analysis. - Guixiang Ma; Chun-Ta Lu; Lifang He 001; Philip S. Yu; Ann B. Ragin (ICDM, 2017)

Kernelized Support Tensor Machines. - Lifang He 001; Chun-Ta Lu; Guixiang Ma; Shen Wang 005; LinLin Shen; Philip S. Yu; Ann B. Ragin (ICML, 2017)

Structural Deep Brain Network Mining. - Shen Wang 005; Lifang He 001; Bokai Cao; Chun-Ta Lu; Philip S. Yu; Ann B. Ragin (KDD, 2017)

t-BNE: Tensor-based Brain Network Embedding. - Bokai Cao; Lifang He 001; Xiaokai Wei; Mengqi Xing; Philip S. Yu; Heide Klumpp; Alex D. Leow (SDM, 2017)

Multilinear Factorization Machines for Multi-Task Multi-View Learning. - Chun-Ta Lu; Lifang He 001; Weixiang Shao; Bokai Cao; Philip S. Yu (WSDM, 2017)

Learning from Multi-View Structural Data via Structural Factorization Machines. - Chun-Ta Lu; Lifang He 001; Hao Ding 003; Philip S. Yu (CoRR, 2017)

Reducing uncertainty of dynamic heterogeneous information networks: a fusing reconstructing approach. - Ning Yang 001; Lifang He 001; Zheng Li; Philip S. Yu (Data Min. Knowl. Discov., 2017)

Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data. - Senzhang Wang; Xiaoming Zhang 001; Jianping Cao; Lifang He 001; Leon Stenneth; Philip S. Yu; Zhoujun Li 001; Zhiqiu Huang (ACM Trans. Inf. Syst., 2017)

Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis. - Ye Liu 006; Lifang He 001; Bokai Cao; Philip S. Yu; Ann B. Ragin; Alex D. Leow (AAAI, 2018)

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease. - Xi Zhang; Lifang He 001; Kun Chen 002; Yuan Luo 001; Jiayu Zhou; Fei Wang 001 (AMIA, 2018)

PER: A Probabilistic Attentional Model for Personalized Text Recommendations. - Lei Zheng 001; Yixue Wang; Lifang He 001; Sihong Xie; Fengjiao Wang; Philip S. Yu (IEEE BigData, 2018)

Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks. - Lichao Sun 001; Lifang He 001; Zhipeng Huang 001; Bokai Cao; Congying Xia; Xiaokai Wei; Philip S. Yu (ICBK, 2018)

A Self-Organizing Tensor Architecture for Multi-view Clustering. - Lifang He 001; Chun-Ta Lu; Yong Chen 016; Jiawei Zhang 001; Linlin Shen; Philip S. Yu; Fei Wang 001 (ICDM, 2018)

SSDMV: Semi-Supervised Deep Social Spammer Detection by Multi-view Data Fusion. - Chaozhuo Li; Senzhang Wang; Lifang He 001; Philip S. Yu; Yanbo Liang; Zhoujun Li 001 (ICDM, 2018)

Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. - Jianguo Zhang 005; Ji Wang 002; Lifang He 001; Zhao Li 007; Philip S. Yu (ICDM, 2018)

Multi-View Fusion Through Cross-Modal Retrieval. - Limeng Cui; Zhensong Chen 001; Jiawei Zhang 001; Lifang He 001; Yong Shi 001; Philip S. Yu (ICIP, 2018)

Multi-view Collective Tensor Decomposition for Cross-modal Hashing. - Limeng Cui; Zhensong Chen 001; Jiawei Zhang 001; Lifang He 001; Yong Shi 001; Philip S. Yu (ICMR, 2018)

Boosted Sparse and Low-Rank Tensor Regression. - Lifang He 001; Kun Chen 002; Wanwan Xu; Jiayu Zhou; Fei Wang 001 (NeurIPS, 2018)

On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation. - Fei Jiang; Lifang He 001; Yi Zheng; Enqiang Zhu; Jin Xu 002; Philip S. Yu (SDM, 2018)

Learning from Multi-View Multi-Way Data via Structural Factorization Machines. - Chun-Ta Lu; Lifang He 001; Hao Ding 003; Bokai Cao; Philip S. Yu (WWW, 2018)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; Vahid Noroozi; He Huang 008; Philip S. Yu (CoRR, 2018)

MARS: Memory Attention-Aware Recommender System. - Lei Zheng 001; Chun-Ta Lu; Lifang He 001; Sihong Xie; He Huang 008; Chaozhuo Li; Vahid Noroozi; Bowen Dong; Philip S. Yu (DSAA, 2019)

Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization. - Mehrnaz Najafi; Lifang He 001; Philip S. Yu (IJCAI, 2019)

Coupled Tensor Decomposition for User Clustering in Mobile Internet Traffic Interaction Pattern. - Ke Yu; Lifang He 001; Philip S. Yu; Wenkai Zhang; Yue Liu 002 (IEEE Access, 2019)

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. - Hao Peng 001; Jianxin Li 002; Qiran Gong; Senzhang Wang; Lifang He 001; Bo Li 005; Lihong Wang; Philip S. Yu (CoRR, 2019)

Multi-view collective tensor decomposition for cross-modal hashing. - Limeng Cui; Jiawei Zhang 001; Lifang He 001; Philip S. Yu (Int. J. Multim. Inf. Retr., 2019)

Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification. - Hao Peng 001; Jianxin Li 002; Qiran Gong; Yuanxing Ning; Senzhang Wang; Lifang He 001 (AAAI, 2020)

Heterogeneous Similarity Graph Neural Network on Electronic Health Records. - Zheng Liu 017; Xiaohan Li 001; Hao Peng 001; Lifang He 001; Philip S. Yu (IEEE BigData, 2020)

Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation. - Zhongfen Deng; Hao Peng 001; Congying Xia; Jianxin Li 002; Lifang He 001; Philip S. Yu (COLING, 2020)

Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks. - Lichao Sun 001; Congying Xia; Wenpeng Yin 001; Tingting Liang; Philip S. Yu; Lifang He 001 (COLING, 2020)

Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks. - Qingyun Sun; Hao Peng 001; Jianxin Li 002; Senzhang Wang; Xiangyu Dong 002; Liangxuan Zhao; Philip S. Yu; Lifang He 001 (ICDM, 2020)

A Survey on Text Classification: From Shallow to Deep Learning. - Qian Li 033; Hao Peng 001; Jianxin Li 002; Congying Xia; Renyu Yang; Lichao Sun 001; Philip S. Yu; Lifang He 001 (CoRR, 2020)

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. - Hao Peng 001; Jianxin Li 002; Zheng Wang 001; Renyu Yang; Mingzhe Liu 002; Mingming Zhang; Philip S. Yu; Lifang He 001 (CoRR, 2020)

Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks. - Lichao Sun 001; Congying Xia; Wenpeng Yin 001; Tingting Liang; Philip S. Yu; Lifang He 001 (CoRR, 2020)

A Comprehensive Comparison of Multi-Dimensional Image Denoising Methods. - Zhaoming Kong; Xiaowei Yang 003; Lifang He 001 (CoRR, 2020)

CAMAR: a broad learning based context-aware recommender for mobile applications. - Tingting Liang; Lifang He 001; Chun-Ta Lu; Liang Chen 001; Haochao Ying; Philip S. Yu; Jian Wu 001 (Knowl. Inf. Syst., 2020)

KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning. - Ye Liu 006; Yao Wan 001; Lifang He 001; Hao Peng 001; Philip S. Yu (AAAI, 2021)

Adversarial Directed Graph Embedding. - Shijie Zhu; Jianxin Li 002; Hao Peng 001; Senzhang Wang; Lifang He 001 (AAAI, 2021)

HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization. - Ye Liu 006; Jian-Guo Zhang 005; Yao Wan 001; Congying Xia; Lifang He 001; Philip S. Yu (EMNLP (1), 2021)

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering. - Jie Xu 044; Yazhou Ren 001; Huayi Tang; Xiaorong Pu; Xiaofeng Zhu 001; Ming Zeng 009; Lifang He 001 (ICCV, 2021)

Outlier-Robust Multi-View Subspace Clustering with Prior Constraints. - Mehrnaz Najafi; Lifang He 001; Philip S. Yu (ICDM, 2021)

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks. - Gongxu Luo; Jianxin Li 002; Hao Peng 001; Carl Yang 001; Lichao Sun 001; Philip S. Yu; Lifang He 001 (IJCAI, 2021)

Non-Linear Fusion for Self-Paced Multi-View Clustering. - Zongmo Huang; Yazhou Ren 001; Xiaorong Pu; Lifang He 001 (ACM Multimedia, 2021)

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. - Qingyun Sun; Jianxin Li 002; Hao Peng 001; Jia Wu 001; Yuanxing Ning; Philip S. Yu; Lifang He 001 (WWW, 2021)

Federated Depression Detection from Multi-SourceMobile Health Data. - Xiaohang Xu 002; Hao Peng 001; Lichao Sun 001; Yan Niu; Hongyuan Ma; Lianzhong Liu; Lifang He 001 (CoRR, 2021)

Federated Multi-View Learning for Private Medical Data Integration and Analysis. - Sicong Che; Hao Peng 001; Lichao Sun 001; Yong Chen 016; Lifang He 001 (CoRR, 2021)

Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities. - Mehrnaz Najafi; Lifang He 001; Philip S. Yu (CoRR, 2021)

Contrastive Multi-Modal Clustering. - Jie Xu 044; Huayi Tang; Yazhou Ren 001; Xiaofeng Zhu 001; Lifang He 001 (CoRR, 2021)

BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis. - Hejie Cui; Wei Dai 013; Yanqiao Zhu 001; Xiaoxiao Li; Lifang He 001; Carl Yang 001 (CoRR, 2021)

Multiplex Graph Networks for Multimodal Brain Network Analysis. - Zhaoming Kong; Lichao Sun 001; Hao Peng 001; Liang Zhan; Yong Chen 016; Lifang He 001 (CoRR, 2021)

Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning. - Hao Peng 001; Bowen Du 001; Mingsheng Liu; Mingzhe Liu 002; Shumei Ji; Senzhang Wang; Xu Zhang; Lifang He 001 (Inf. Sci., 2021)

CommPOOL: An interpretable graph pooling framework for hierarchical graph representation learning. - Haoteng Tang; Guixiang Ma; Lifang He 001; Heng Huang; Liang Zhan (Neural Networks, 2021)

Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks. - Hao Peng 001; Jianxin Li 002; Yangqiu Song; Renyu Yang; Rajiv Ranjan 001; Philip S. Yu; Lifang He 001 (ACM Trans. Knowl. Discov. Data, 2021)

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. - Hao Peng 001; Jianxin Li 002; Senzhang Wang; Lihong Wang; Qiran Gong; Renyu Yang; Bo Li 005; Philip S. Yu; Lifang He 001 (IEEE Trans. Knowl. Data Eng., 2021)

MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types. - Linchuan Xu; Jing Wang 023; Lifang He 001; Jiannong Cao 001; Xiaokai Wei; Philip S. Yu; Kenji Yamanishi (IEEE Trans. Knowl. Data Eng., 2021)

Multi-View Brain Network Analysis with Cross-View Missing Network Generation. - Gongxu Luo; Chenyang Li; Hejie Cui; Lichao Sun 001; Lifang He 001; Carl Yang 001 (BIBM, 2022)

Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer's Disease Prediction. - Jun Yu; Benjamin Zalatan; Yong Chen 016; Li Shen 001; Lifang He 001 (BIBM, 2022)

BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks (Extended Abstract). - Hejie Cui; Wei Dai 013; Yanqiao Zhu 001; Xuan Kan; Antonio Aodong Chen Gu; Joshua Lukemire; Liang Zhan; Lifang He 001; Ying Guo 003; Carl Yang 001 (IEEE Big Data, 2022)

From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection. - Jiaqian Ren; Lei Jiang 003; Hao Peng 001; Yuwei Cao; Jia Wu 001; Philip S. Yu; Lifang He 001 (CIKM, 2022)

Multi-level Feature Learning for Contrastive Multi-view Clustering. - Jie Xu 044; Huayi Tang; Yazhou Ren 001; Liang Peng; Xiaofeng Zhu 001; Lifang He 001 (CVPR, 2022)

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis. - Yanqiao Zhu 001; Hejie Cui; Lifang He 001; Lichao Sun 001; Carl Yang 001 (EMBC, 2022)

ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. - Yao Su 003; Xin Dai; Lifang He 001; Xiangnan Kong (ICDM, 2022)

Shared-Attribute Multi-Graph Clustering with Global Self-Attention. - Jianpeng Chen; Zhimeng Yang; Jingyu Pu; Yazhou Ren 001; Xiaorong Pu; Li Gao; Lifang He 001 (ICONIP (1), 2022)

Structure-Preserving Graph Kernel for Brain Network Classification. - Jun Yu; Zhaoming Kong; Aditya Kendre; Hao Peng 001; Carl Yang 001; Lichao Sun 001; Alex D. Leow; Lifang He 001 (ISBI, 2022)

Interpretable Graph Convolutional Network Of Multi-Modality Brain Imaging For Alzheimer's Disease Diagnosis. - Houliang Zhou; Lifang He 001; Yu Zhang 009; Li Shen 001; Brian Chen (ISBI, 2022)

ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. - Yao Su 003; Zhentian Qian; Lifang He 001; Xiangnan Kong (KDD, 2022)

Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. - Yi Yang 094; Yanqiao Zhu 001; Hejie Cui; Xuan Kan; Lifang He 001; Ying Guo 003; Carl Yang 001 (KDD, 2022)

Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. - Hejie Cui; Wei Dai 013; Yanqiao Zhu 001; Xiaoxiao Li; Lifang He 001; Carl Yang 001 (MICCAI (8), 2022)

Sparse Interpretation of Graph Convolutional Networks for Multi-modal Diagnosis of Alzheimer's Disease. - Houliang Zhou; Yu Zhang 009; Brian Y. Chen; Li Shen 001; Lifang He 001 (MICCAI (8), 2022)

Intelligent classification of antenatal cardiotocography signals via multimodal bidirectional gated recurrent units. - Yue Fei; Fan Chen; Lifang He 001; Jiamin Chen; Yuexing Hao; Xia Li 008; Guiqing Liu; Qinqun Chen; Li Li; Hang Wei 001 (Biomed. Signal Process. Control., 2022)

Task Modifiers for HTN Planning and Acting. - Weihang Yuan; Hector Muñoz-Avila; Venkatsampath Raja Gogineni; Sravya Kondrakunta; Michael T. Cox; Lifang He 001 (CoRR, 2022)

Deep learning for drug repurposing: methods, databases, and applications. - Xiaoqin Pan; Xuan Lin; Dongsheng Cao 001; Xiangxiang Zeng; Philip S. Yu; Lifang He 001; Ruth Nussinov; Feixiong Cheng (CoRR, 2022)

Deep Embedded Multi-View Clustering via Jointly Learning Latent Representations and Graphs. - Zongmo Huang; Yazhou Ren 001; Xiaorong Pu; Lifang He 001 (CoRR, 2022)

Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis. - Jun Yu; Zhaoming Kong; Liang Zhan; Li Shen 001; Lifang He 001 (CoRR, 2022)

Variational Graph Generator for Multi-View Graph Clustering. - Jianpeng Chen; Yawen Ling; Jie Xu 044; Yazhou Ren 001; Shudong Huang; Xiaorong Pu; Lifang He 001 (CoRR, 2022)

Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease. - Xuetong Wang; Kanhao Zhao; Rong Zhou; Alex D. Leow; Ricardo Osorio; Yu Zhang 009; Lifang He 001 (CoRR, 2022)

Cross-knowledge-graph entity alignment via relation prediction. - Hongren Huang; Chen Li 046; Xutan Peng; Lifang He 001; Shu Guo; Hao Peng 001; Lihong Wang; Jianxin Li 002 (Knowl. Based Syst., 2022)

Context-aware road travel time estimation by coupled tensor decomposition based on trajectory data. - Liping Huang; Yongjian Yang 001; Hechang Chen; Yunke Zhang; Zijia Wang; Lifang He 001 (Knowl. Based Syst., 2022)

A transfer learning-based novel fusion convolutional neural network for breast cancer histology classification. - Xiangchun Yu; Hechang Chen; Miaomiao Liang; Qing Xu; Lifang He 001 (Multim. Tools Appl., 2022)

Deep reinforcement learning guided graph neural networks for brain network analysis. - Xusheng Zhao; Jia Wu 001; Hao Peng 001; Amin Beheshti; Jessica J. M. Monaghan; David McAlpine; Heivet Hernandez-Perez; Mark Dras; Qiong Dai; Yangyang Li; Philip S. Yu; Lifang He 001 (Neural Networks, 2022)

Lime: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. - Hao Peng 001; Renyu Yang; Zheng Wang 001; Jianxin Li 002; Lifang He 001; Philip S. Yu; Albert Y. Zomaya; Rajiv Ranjan 001 (IEEE Trans. Computers, 2022)

Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data. - Xiaohang Xu 002; Hao Peng 001; Md. Zakirul Alam Bhuiyan; Zhifeng Hao; Lianzhong Liu; Lichao Sun 001; Lifang He 001 (IEEE Trans. Ind. Informatics, 2022)

Federated Multi-view Learning for Private Medical Data Integration and Analysis. - Sicong Che; Zhaoming Kong; Hao Peng 001; Lichao Sun 001; Alex D. Leow; Yong Chen 016; Lifang He 001 (ACM Trans. Intell. Syst. Technol., 2022)

A Survey on Text Classification: From Traditional to Deep Learning. - Qian Li 033; Hao Peng 001; Jianxin Li 002; Congying Xia; Renyu Yang; Lichao Sun 001; Philip S. Yu; Lifang He 001 (ACM Trans. Intell. Syst. Technol., 2022)

Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph. - Chen Li 046; Hao Peng 001; Jianxin Li 002; Lichao Sun 001; Lingjuan Lyu; Lihong Wang; Philip S. Yu; Lifang He 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering. - Zongmo Huang; Yazhou Ren 001; Xiaorong Pu; Shudong Huang; Zenglin Xu; Lifang He 001 (AAAI, 2023)

Dual Label-Guided Graph Refinement for Multi-View Graph Clustering. - Yawen Ling; Jianpeng Chen; Yazhou Ren 001; Xiaorong Pu; Jie Xu 044; Xiaofeng Zhu 001; Lifang He 001 (AAAI, 2023)

Interpretable Graph Convolutional Network for Alzheimer's Disease Diagnosis using Multi-Modal Imaging Genetics. - Houliang Zhou; Yu Zhang 009; Lifang He 001; Li Shen 001; Brian Y. Chen (BIBM, 2023)

Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics. - Rong Zhou; Houliang Zhou; Li Shen 001; Brian Y. Chen; Yu Zhang 009; Lifang He 001 (BIBM, 2023)

Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. - Guangjie Zeng; Hao Peng 001; Angsheng Li; Zhiwei Liu 001; Chunyang Liu; Philip S. Yu; Lifang He 001 (ICDM, 2023)

Deep Multi-view Subspace Clustering with Anchor Graph. - Chenhang Cui; Yazhou Ren 001; Jingyu Pu; Xiaorong Pu; Lifang He 001 (IJCAI, 2023)

Hierarchical State Abstraction based on Structural Information Principles. - Xianghua Zeng; Hao Peng 001; Angsheng Li; Chunyang Liu; Lifang He 001; Philip S. Yu (IJCAI, 2023)

Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease. - Xuetong Wang; Rong Zhou; Kanhao Zhao; Alex D. Leow; Yu Zhang 009; Lifang He 001 (ISBI, 2023)

One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. - Yao Su 003; Zhentian Qian; Lei Ma; Lifang He 001; Xiangnan Kong (KDD, 2023)

Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics. - Rong Zhou; Houliang Zhou; Brian Y. Chen; Li Shen 001; Yu Zhang 009; Lifang He 001 (MICCAI (2), 2023)

Federated Deep Multi-View Clustering with Global Self-Supervision. - Xinyue Chen; Jie Xu 044; Yazhou Ren 001; Xiaorong Pu; Ce Zhu; Xiaofeng Zhu 001; Zhifeng Hao; Lifang He 001 (ACM Multimedia, 2023)

Generative Neutral Features-Disentangled Learning for Facial Expression Recognition. - Zhenqian Wu; Yazhou Ren 001; Xiaorong Pu; Zhifeng Hao; Lifang He 001 (ACM Multimedia, 2023)

A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective. - Chenhang Cui; Yazhou Ren 001; Jingyu Pu; Jiawei Li; Xiaorong Pu; Tianyi Wu; Yutao Shi; Lifang He 001 (NeurIPS, 2023)

A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. - Ce Zhou; Qian Li 033; Chen Li 046; Jun Yu; Yixin Liu 002; Guangjing Wang 001; Kai Zhang 039; Cheng Ji 001; Qiben Yan; Lifang He 001; Hao Peng 001; Jianxin Li 002; et al. (CoRR, 2023)

Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition. - Zhenqian Wu; Xiaoyuan Li; Yazhou Ren 001; Xiaorong Pu; Xiaofeng Zhu 001; Lifang He 001 (CoRR, 2023)

A Comparison of Image Denoising Methods. - Zhaoming Kong; Fangxi Deng; Haomin Zhuang; Xiaowei Yang 003; Jun Yu; Lifang He 001 (CoRR, 2023)

BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks. - Kai Zhang 039; Jun Yu; Zhiling Yan; Yixin Liu 002; Eashan Adhikarla; Sunyang Fu; Xun Chen; Chen Chen 001; Yuyin Zhou; Xiang Li 001; Lifang He 001; Brian D. Davison 001; et al. (CoRR, 2023)

Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V. - Zhiling Yan; Kai Zhang 039; Rong Zhou; Lifang He 001; Xiang Li 001; Lichao Sun 001 (CoRR, 2023)

Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. - Jianxin Li 002; Hao Peng 001; Yuwei Cao; Yingtong Dou; Hekai Zhang; Philip S. Yu; Lifang He 001 (IEEE Trans. Knowl. Data Eng., 2023)

Learning from undercoded clinical records for automated International Classification of Diseases (ICD) coding. - Yucheng Jin; Yun Xiong; Dan Shi; Yifei Lin; Lifang He 001; Yao Zhang 009; Joseph M. Plasek; Li Zhou 007; David W. Bates; Chunlei Tang (J. Am. Medical Informatics Assoc., 2023)

BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks. - Hejie Cui; Wei Dai 013; Yanqiao Zhu 001; Xuan Kan; Antonio Aodong Chen Gu; Joshua Lukemire; Liang Zhan; Lifang He 001; Ying Guo 003; Carl Yang 001 (IEEE Trans. Medical Imaging, 2023)

DC-FUDA: Improving deep clustering via fully unsupervised domain adaptation. - Zhimeng Yang; Yazhou Ren 001; Zirui Wu; Ming Zeng 009; Jie Xu 044; Yang Yang 002; Xiaorong Pu; Philip S. Yu; Lifang He 001 (Neurocomputing, 2023)

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. - Hao Peng 001; Jianxin Li 002; Zheng Wang 001; Renyu Yang; Mingsheng Liu; Mingming Zhang; Philip S. Yu; Lifang He 001 (IEEE Trans. Knowl. Data Eng., 2023)

BayesKGR: Bayesian Few-Shot Learning for Knowledge Graph Reasoning. - Feng Zhao 003; Cheng Yan; Hai Jin 001; Lifang He 001 (ACM Trans. Asian Low Resour. Lang. Inf. Process., 2023)

Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering. - Jie Xu 044; Yazhou Ren 001; Huayi Tang; Zhimeng Yang; Lili Pan 001; Yang Yang 002; Xiaorong Pu; Philip S. Yu; Lifang He 001 (IEEE Trans. Knowl. Data Eng., 2023)

Adversarial Attack and Defense on Graph Data: A Survey. - Lichao Sun 001; Yingtong Dou; Carl Yang 001; Kai Zhang 039; Ji Wang 002; Philip S. Yu; Lifang He 001; Bo Li 026 (IEEE Trans. Knowl. Data Eng., 2023)

A Robust and Generalized Framework for Adversarial Graph Embedding. - Jianxin Li 002; Xingcheng Fu; Shijie Zhu; Hao Peng 001; Senzhang Wang; Qingyun Sun; Philip S. Yu; Lifang He 001 (IEEE Trans. Knowl. Data Eng., 2023)

Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. - Jianxin Li 002; Lifang He 001; Hao Peng 001; Peng Cui 001; Charu C. Aggarwal; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2023)

Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. - Jingyu Pu; Chenhang Cui; Xinyue Chen; Yazhou Ren 001; Xiaorong Pu; Zhifeng Hao; Philip S. Yu; Lifang He 001 (AAAI, 2024)

Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering. - Zichen Wen; Yawen Ling; Yazhou Ren 001; Tianyi Wu; Jianpeng Chen; Xiaorong Pu; Zhifeng Hao; Lifang He 001 (AAAI, 2024)

BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations. - Kaiqiao Han; Yi Yang 001; Zijie Huang 002; Xuan Kan; Ying Guo 003; Yang Yang 009; Lifang He 001; Liang Zhan; Yizhou Sun; Wei Wang 010; Carl Yang 001 (BHI, 2024)

VGG-ST: A VGG-Swin Transformer-Based Model for ROP Disease Diagnosis. - Xinwei Luo; Songlin Zhao; Yong Chen 016; Gui-Shuang Ying; Lifang He 001 (BIBM, 2024)

Position: TrustLLM: Trustworthiness in Large Language Models. - Yue Huang; Lichao Sun 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Yuan Li; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang; Xiner Li; Hanchi Sun; et al. (ICML, 2024)

Dynamic Weighted Graph Fusion for Deep Multi-View Clustering. - Yazhou Ren 001; Jingyu Pu; Chenhang Cui; Yan Zheng; Xinyue Chen; Xiaorong Pu; Lifang He 001 (IJCAI, 2024)

Integrating Vision-Language Semantic Graphs in Multi-View Clustering. - JunLong Ke; Zichen Wen; Yechenhao Yang; Chenhang Cui; Yazhou Ren 001; Xiaorong Pu; Lifang He 001 (IJCAI, 2024)

Cross-View Contrastive Fusion for Enhanced Molecular Property Prediction. - Yan Zheng; Song Wu; Junyu Lin; Yazhou Ren 001; Jing He 004; Xiaorong Pu; Lifang He 001 (IJCAI, 2024)

Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation. - Haoteng Tang; Guodong Liu; Siyuan Dai; Kai Ye 002; Kun Zhao 007; Wenlu Wang; Carl Yang 001; Lifang He 001; Alex D. Leow; Paul M. Thompson; Heng Huang; Liang Zhan (MICCAI (2), 2024)

Normative Modeling with Focal Loss and Adversarial Autoencoders for Alzheimer's Disease Diagnosis and Biomarker Identification. - Songlin Zhao; Rong Zhou; Yu Zhang 009; Yong Chen 016; Lifang He 001 (AMAI@MICCAI, 2024)

Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering. - Zichen Wen; Tianyi Wu; Yazhou Ren 001; Yawen Ling; Chenhang Cui; Xiaorong Pu; Lifang He 001 (ACM Multimedia, 2024)

Semi-Supervised Clustering via Structural Entropy with Different Constraints. - Guangjie Zeng; Hao Peng 001; Angsheng Li; Zhiwei Liu 001; Runze Yang; Chunyang Liu; Lifang He 001 (SDM, 2024)

TGNet: tensor-based graph convolutional networks for multimodal brain network analysis. - Zhaoming Kong; Rong Zhou; Xinwei Luo; Songlin Zhao; Ann B. Ragin; Alex D. Leow; Lifang He 001 (BioData Min., 2024)

TrustLLM: Trustworthiness in Large Language Models. - Lichao Sun 001; Yue Huang 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang 001; Xiner Li; Zhengliang Liu; Yixin Liu 002; et al. (CoRR, 2024)

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models. - Yixin Liu 002; Kai Zhang 039; Yuan Li 032; Zhiling Yan; Chujie Gao; Ruoxi Chen; Zhengqing Yuan; Yue Huang 001; Hanchi Sun; Jianfeng Gao 001; Lifang He 001; Lichao Sun 001 (CoRR, 2024)

Mora: Enabling Generalist Video Generation via A Multi-Agent Framework. - Zhengqing Yuan; Ruoxi Chen; Zhaoxu Li; Haolong Jia; Lifang He 001; Chi Wang; Lichao Sun 001 (CoRR, 2024)

ViT-1.58b: Mobile Vision Transformers in the 1-bit Era. - Zhengqing Yuan; Rong Zhou; Hongyi Wang 001; Lifang He 001; Yanfang Ye 001; Lichao Sun 001 (CoRR, 2024)

Bora: Biomedical Generalist Video Generation Model. - Weixiang Sun; Xiaocao You; Ruizhe Zheng; Zhengqing Yuan; Xiang Li 001; Lifang He 001; Quanzheng Li; Lichao Sun 001 (CoRR, 2024)

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos. - Zhiling Yan; Weixiang Sun; Rong Zhou; Zhengqing Yuan; Kai Zhang 039; Yiwei Li 002; Tianming Liu 001; Quanzheng Li; Xiang Li 001; Lifang He 001; Lichao Sun 001 (CoRR, 2024)

TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation. - Rong Zhou; Zhengqing Yuan; Zhiling Yan; Weixiang Sun; Kai Zhang 039; Yiwei Li 002; Yanfang Ye 001; Xiang Li 001; Lifang He 001; Lichao Sun 001 (CoRR, 2024)

SiMilarity-Enhanced Homophily for Multi-View Heterophilous Graph Clustering. - Jianpeng Chen; Yawen Ling; Yazhou Ren 001; Zichen Wen; Tianyi Wu; Shufei Zhang; Lifang He 001 (CoRR, 2024)

Normative Modeling for AD Diagnosis and Biomarker Identification. - Songlin Zhao; Rong Zhou; Yu Zhang 009; Yong Chen 016; Lifang He 001 (CoRR, 2024)

Political-LLM: Large Language Models in Political Science. - Lincan Li; Jiaqi Li; Catherine Chen 003; Fred Gui; Hongjia Yang; Chenxiao Yu; Zhengguang Wang; Jianing Cai; Junlong Aaron Zhou; Bolin Shen; Alex Qian; Weixin Chen; et al. (CoRR, 2024)

A Contrastive-Enhanced Ensemble Framework for Efficient Multi-Agent Reinforcement Learning. - Xinqi Du; Hechang Chen; Yongheng Xing; Philip S. Yu; Lifang He 001 (Expert Syst. Appl., 2024)

A novel federated multi-view clustering method for unaligned and incomplete data fusion. - Yazhou Ren 001; Xinyue Chen; Jie Xu 044; Jingyu Pu; Yonghao Huang; Xiaorong Pu; Ce Zhu; Xiaofeng Zhu 001; Zhifeng Hao; Lifang He 001 (Inf. Fusion, 2024)

A Multilinear Least-Squares Formulation for Sparse Tensor Canonical Correlation Analysis. - Jun Yu; Zhaoming Kong; Kun Chen 002; Xin Zhang; Yong Chen 016; Lifang He 001 (Trans. Mach. Learn. Res., 2024)

Self-Weighted Contrastive Fusion for Deep Multi-View Clustering. - Song Wu; Yan Zheng; Yazhou Ren 001; Jing He 004; Xiaorong Pu; Shudong Huang; Zhifeng Hao; Lifang He 001 (IEEE Trans. Multim., 2024)

Robust multi-agent reinforcement learning via Bayesian distributional value estimation. - Xinqi Du; Hechang Chen; Che Wang; Yongheng Xing; Jielong Yang; Philip S. Yu; Yi Chang 001; Lifang He 001 (Pattern Recognit., 2024)

Comprehensive Multiview Representation Learning via Deep Autoencoder-Like Nonnegative Matrix Factorization. - Haonan Huang; Guoxu Zhou; Qibin Zhao; Lifang He 001; Shengli Xie (IEEE Trans. Neural Networks Learn. Syst., 2024)

SegImgNet: Segmentation-Guided Dual-Branch Network for Retinal Disease Diagnoses. - Xinwei Luo; Songlin Zhao; Yun Zong; Yong Chen 016; Gui-Shuang Ying; Lifang He 001 (AAAI Spring Symposia, 2025)

End-to-End Deep Learning for Structural Brain Imaging: A Unified Framework. - Yao Su 003; Keqi Han; Mingjie Zeng; Lichao Sun 001; Liang Zhan; Carl Yang 001; Lifang He 001; Xiangnan Kong (AAAI Spring Symposia, 2025)

Multi-modal isolated sign language recognition based on self-paced learning. - Yazhou Ren 001; Hongkai Li; Yuhao Li; Jingyu Pu; Xiaorong Pu; Siyuan Jing; Peng Jin; Lifang He 001 (Expert Syst. Appl., 2025)

Large Language Models for Bioinformatics. - Wei Ruan; Yanjun Lyu; Jing Zhang 010; Jiazhang Cai; Peng Shu; Yang Ge; Yao Lu; Shang Gao; Yue Wang; Peilong Wang; Lin Zhao 004; Tao Wang; et al. (CoRR, 2025)

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? - Keqi Han; Yao Su 003; Lifang He 001; Liang Zhan; Sergey M. Plis; Vince D. Calhoun; Carl Yang 001 (CoRR, 2025)

Multi-Modal Diagnosis of Alzheimer's Disease Using Interpretable Graph Convolutional Networks. - Houliang Zhou; Lifang He 001; Brian Y. Chen; Li Shen 001; Yu Zhang 009 (IEEE Trans. Medical Imaging, 2025)

ClusMFL: A Cluster-Enhanced Framework for Modality-Incomplete Multimodal Federated Learning in Brain Imaging Analysis. - Xinpeng Wang; Rong Zhou; Han Xie; Xiaoying Tang; Lifang He 001; Carl Yang 001 (CoRR, 2025)

A Survey on Post-training of Large Language Models. - Guiyao Tie; Zeli Zhao; Dingjie Song; Fuyang Wei; Rong Zhou; Yurou Dai; Wen Yin; Zhejian Yang; Jiangyue Yan; Yao Su 003; Zhenhan Dai; Yifeng Xie; et al. (CoRR, 2025)

Deep Clustering: A Comprehensive Survey. - Yazhou Ren 001; Jingyu Pu; Zhimeng Yang; Jie Xu 044; Guofeng Li; Xiaorong Pu; Philip S. Yu; Lifang He 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

EfficientLLM: Efficiency in Large Language Models. - Zhengqing Yuan; Weixiang Sun; Yixin Liu 002; Huichi Zhou; Rong Zhou; Yiyang Li; Zheyuan Zhang; Wei Song; Yue Huang; Haolong Jia; Keerthiram Murugesan; Yu Wang; et al. (CoRR, 2025)

A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning for Any Atlas and Disorder. - Xinxu Wei; Kanhao Zhao; Yong Jiao; Lifang He 001; Yu Zhang (CoRR, 2025)

Towards a general-purpose foundation model for fMRI analysis. - Cheng Wang; Yu Jiang; Zhihao Peng 002; Chenxin Li; Changbae Bang; Lin Zhao 004; Jinglei Lv; Jorge Sepulcre; Carl Yang 001; Lifang He 001; Tianming Liu 001; Daniel Barron; et al. (CoRR, 2025)

Variational Graph Generator for Multiview Graph Clustering. - Jianpeng Chen; Yawen Ling; Jie Xu 044; Yazhou Ren 001; Shudong Huang; Xiaorong Pu; Zhifeng Hao; Philip S. Yu; Lifang He 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

SAMed-2: Selective Memory Enhanced Medical Segment Anything Model. - Zhiling Yan; Sifan Song; Dingjie Song; Yiwei Li 002; Rong Zhou; Weixiang Sun; Zhennong Chen; Sekeun Kim; Hui Ren 001; Tianming Liu 001; Quanzheng Li; Xiang Li 001; et al. (CoRR, 2025)

A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments. - Yuchen Wang; Hongjue Zhao; Haohong Lin; Enze Xu; Lifang He 001; Huajie Shao (CoRR, 2025)