Lifang He
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
70
Venues
22
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
70 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | Multi-View Graph Clustering via Node-Guided Contrastive Encoding. | Yazhou Ren, Junlong Ke, Zichen Wen, Tianyi Wu, Yang Yang, Xiaorong Pu, Lifang He |
| 2025 | ICML | 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, Huajie Shao |
| 2025 | ICML | Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG. | Xinxu Wei, Kanhao Zhao, Yong Jiao, Hua Xie, Lifang He, Yu Zhang |
| 2025 | MICCAI | SAMed-2: Selective Memory Enhanced Medical Segment Anything Model. | Zhiling Yan, Sifan Song, Dingjie Song, Yiwei Li, Rong Zhou, Weixiang Sun, Zhennong Chen, Sekeun Kim, Hui Ren, Tianming Liu, Quanzheng Li, Xiang Li, Lifang He, Lichao Sun |
| 2024 | AAAI | Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. | Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He |
| 2024 | AAAI | Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering. | Zichen Wen, Yawen Ling, Yazhou Ren, Tianyi Wu, Jianpeng Chen, Xiaorong Pu, Zhifeng Hao, Lifang He |
| 2024 | ICML | Position: TrustLLM: Trustworthiness in Large Language Models. | Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao |
| 2024 | IJCAI | Dynamic Weighted Graph Fusion for Deep Multi-View Clustering. | Yazhou Ren, Jingyu Pu, Chenhang Cui, Yan Zheng, Xinyue Chen, Xiaorong Pu, Lifang He |
| 2024 | IJCAI | Integrating Vision-Language Semantic Graphs in Multi-View Clustering. | Junlong Ke, Zichen Wen, Yechenhao Yang, Chenhang Cui, Yazhou Ren, Xiaorong Pu, Lifang He |
| 2024 | IJCAI | Cross-View Contrastive Fusion for Enhanced Molecular Property Prediction. | Yan Zheng, Song Wu, Junyu Lin, Yazhou Ren, Jing He, Xiaorong Pu, Lifang He |
| 2024 | MICCAI | Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation. | Haoteng Tang, Guodong Liu, Siyuan Dai, Kai Ye, Kun Zhao, Wenlu Wang, Carl Yang, Lifang He, Alex D. Leow, Paul M. Thompson, Heng Huang, Liang Zhan |
| 2024 | MICCAI | Normative Modeling with Focal Loss and Adversarial Autoencoders for Alzheimer's Disease Diagnosis and Biomarker Identification. | Songlin Zhao, Rong Zhou, Yu Zhang, Yong Chen, Lifang He |
| 2024 | SDM | Semi-Supervised Clustering via Structural Entropy with Different Constraints. | Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He |
| 2023 | AAAI | Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering. | Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He |
| 2023 | AAAI | Dual Label-Guided Graph Refinement for Multi-View Graph Clustering. | Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He |
| 2023 | ICDM | Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. | Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He |
| 2023 | IJCAI | Deep Multi-view Subspace Clustering with Anchor Graph. | Chenhang Cui, Yazhou Ren, Jingyu Pu, Xiaorong Pu, Lifang He |
| 2023 | IJCAI | Hierarchical State Abstraction based on Structural Information Principles. | Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu |
| 2023 | KDD | One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. | Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong |
| 2023 | MICCAI | Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics. | Rong Zhou, Houliang Zhou, Brian Y. Chen, Li Shen, Yu Zhang, Lifang He |
| 2022 | CIKM | From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection. | Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He |
| 2022 | CVPR | Multi-level Feature Learning for Contrastive Multi-view Clustering. | Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He |
| 2022 | ICDM | ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. | Yao Su, Xin Dai, Lifang He, Xiangnan Kong |
| 2022 | ICONIP | Shared-Attribute Multi-Graph Clustering with Global Self-Attention. | Jianpeng Chen, Zhimeng Yang, Jingyu Pu, Yazhou Ren, Xiaorong Pu, Li Gao, Lifang He |
| 2022 | KDD | ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. | Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong |
| 2022 | KDD | Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. | Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang |
| 2022 | MICCAI | Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. | Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang |
| 2022 | MICCAI | Sparse Interpretation of Graph Convolutional Networks for Multi-modal Diagnosis of Alzheimer's Disease. | Houliang Zhou, Yu Zhang, Brian Y. Chen, Li Shen, Lifang He |
| 2021 | AAAI | KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning. | Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu |
| 2021 | AAAI | Adversarial Directed Graph Embedding. | Shijie Zhu, Jianxin Li, Hao Peng, Senzhang Wang, Lifang He |
| 2021 | EMNLP | HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization. | Ye Liu, Jian-Guo Zhang, Yao Wan, Congying Xia, Lifang He, Philip S. Yu |
| 2021 | ICCV | Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering. | Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He |
| 2021 | ICDM | Outlier-Robust Multi-View Subspace Clustering with Prior Constraints. | Mehrnaz Najafi, Lifang He, Philip S. Yu |
| 2021 | IJCAI | Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks. | Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He |
| 2021 | WWW | SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. | Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He |
| 2020 | AAAI | Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification. | Hao Peng, Jianxin Li, Qiran Gong, Yuanxing Ning, Senzhang Wang, Lifang He |
| 2020 | COLING | Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation. | Zhongfen Deng, Hao Peng, Congying Xia, Jianxin Li, Lifang He, Philip S. Yu |
| 2020 | COLING | Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks. | Lichao Sun, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu, Lifang He |
| 2020 | ICDM | Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks. | Qingyun Sun, Hao Peng, Jianxin Li, Senzhang Wang, Xiangyu Dong, Liangxuan Zhao, Philip S. Yu, Lifang He |
| 2019 | DSAA | MARS: Memory Attention-Aware Recommender System. | Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, He Huang, Chaozhuo Li, Vahid Noroozi, Bowen Dong, Philip S. Yu |
| 2019 | IJCAI | Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization. | Mehrnaz Najafi, Lifang He, Philip S. Yu |
| 2018 | AAAI | Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis. | Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow |
| 2018 | AMIA | Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease. | Xi Zhang, Lifang He, Kun Chen, Yuan Luo, Jiayu Zhou, Fei Wang |
| 2018 | ICDM | A Self-Organizing Tensor Architecture for Multi-view Clustering. | Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang |
| 2018 | ICDM | 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 |
| 2018 | ICDM | Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. | Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu |
| 2018 | ICIP | Multi-View Fusion Through Cross-Modal Retrieval. | Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu |
| 2018 | WWW | Learning from Multi-View Multi-Way Data via Structural Factorization Machines. | Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao, Philip S. Yu |
| 2018 | SDM | On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation. | Fei Jiang, Lifang He, Yi Zheng, Enqiang Zhu, Jin Xu, Philip S. Yu |
| 2017 | CIKM | Multi-view Clustering with Graph Embedding for Connectome Analysis. | Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow, Ann B. Ragin |
| 2017 | CIKM | Coupled Sparse Matrix Factorization for Response Time Prediction in Logistics Services. | Yuqi Wang, Jiannong Cao, Lifang He, Wengen Li, Lichao Sun, Philip S. Yu |
| 2017 | CIKM | Broad Learning based Multi-Source Collaborative Recommendation. | Junxing Zhu, Jiawei Zhang, Lifang He, Quanyuan Wu, Bin Zhou, Chenwei Zhang, Philip S. Yu |
| 2017 | CVPR | Multi-way Multi-level Kernel Modeling for Neuroimaging Classification. | Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin |
| 2017 | ICDM | A Broad Learning Approach for Context-Aware Mobile Application Recommendation. | Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu |
| 2017 | ICDM | Multi-view Graph Embedding with Hub Detection for Brain Network Analysis. | Guixiang Ma, Chun-Ta Lu, Lifang He, Philip S. Yu, Ann B. Ragin |
| 2017 | ICML | Kernelized Support Tensor Machines. | Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, LinLin Shen, Philip S. Yu, Ann B. Ragin |
| 2017 | KDD | Structural Deep Brain Network Mining. | Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin |
| 2017 | WSDM | Multilinear Factorization Machines for Multi-Task Multi-View Learning. | Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao, Philip S. Yu |
| 2017 | SDM | t-BNE: Tensor-based Brain Network Embedding. | Bokai Cao, Lifang He, Xiaokai Wei, Mengqi Xing, Philip S. Yu, Heide Klumpp, Alex D. Leow |
| 2016 | ICDM | Online Unsupervised Multi-view Feature Selection. | Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu |
| 2016 | IJCAI | Item Recommendation for Emerging Online Businesses. | Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He, Philip S. Yu |
| 2016 | IJCNN | Multi-source Multi-view Clustering via discrepancy penalty. | Weixiang Shao, Jiawei Zhang, Lifang He, Philip S. Yu |
| 2016 | KDD | Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. | Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu |
| 2016 | MDM | Estimating Urban Traffic Congestions with Multi-sourced Data. | Senzhang Wang, Lifang He, Leon Stenneth, Philip S. Yu, Zhoujun Li, Zhiqiu Huang |
| 2016 | SDM | Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification. | Guixiang Ma, Lifang He, Chun-Ta Lu, Philip S. Yu, Linlin Shen, Ann B. Ragin |
| 2015 | PAKDD | Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization. | Weixiang Shao, Lifang He, Philip S. Yu |
| 2014 | ICDM | Tensor-Based Multi-view Feature Selection with Applications to Brain Diseases. | Bokai Cao, Lifang He, Xiangnan Kong, Philip S. Yu, Zhifeng Hao, Ann B. Ragin |
| 2014 | ICDM | Low-Density Cut Based Tree Decomposition for Large-Scale SVM Problems. | Lifang He, Hong-Han Shuai, Xiangnan Kong, Zhifeng Hao, Xiaowei Yang, Philip S. Yu |
| 2014 | SDM | DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. | Lifang He, Xiangnan Kong, Philip S. Yu, Xiaowei Yang, Ann B. Ragin, Zhifeng Hao |
| 2010 | SMC | Category of inter-grey non-symmetric evolutionary game chain model of supervision on research funds of colleges and universities. | Hongzhuan Chen, Jing Xu, Lifang He, Ye Chen |