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Semantic ScholarLifang He 0001
何丽芳
Person information
- affiliation: Lehigh University, Bethlehem, PA, USA
- affiliation: University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics, Philadelphia, PA, USA
- affiliation (former): Cornell University, Weill Cornell Medical College, New York, NY, USA
- affiliation (former): Shenzhen University, School of Computer Science and Software Engineering, Computer Vision Institute, China
- affiliation (PhD 2014): South China Institute of Technology, School of Computer Science and Engineering, Guangzhou, China
- unicode name: 何丽芳
Other persons with the same name
- Lifang He 0002 — Central South University, School of Information Science and Engineering, Changsha, China
- Lifang He 0003 — Nanjing University of Aeronautics and Astronautics, College of Economics and Management, China
- Lifang He 0004
![[0000-0002-0014-1845]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-0014-1845")
— Kunming University of Science and Technology, Department of Electronics and Communication Engineering, China
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2020 – today
- 2020
[j13]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu:
CAMAR: a broad learning based context-aware recommender for mobile applications. Knowl. Inf. Syst. 62(8): 3291-3319 (2020)- [c43]Hao Peng, Jianxin Li, Qiran Gong, Yuanxing Ning, Senzhang Wang, Lifang He:
Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification. AAAI 2020: 5387-5394
2010 – 2019
- 2019
- [j12]Ke Yu, Lifang He, Philip S. Yu, Wenkai Zhang, Yue Liu:
Coupled Tensor Decomposition for User Clustering in Mobile Internet Traffic Interaction Pattern. IEEE Access 7: 18113-18124 (2019) - [j11]Limeng Cui, Jiawei Zhang, Lifang He, Philip S. Yu:
Multi-view collective tensor decomposition for cross-modal hashing. Int. J. Multim. Inf. Retr. 8(1): 47-59 (2019) - [c42]Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, He Huang, Chaozhuo Li, Vahid Noroozi, Bowen Dong, Philip S. Yu:
MARS: Memory Attention-Aware Recommender System. DSAA 2019: 11-20 - [c41]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization. IJCAI 2019: 3187-3194 - [i19]Hao Peng, Jianxin Li, Qiran Gong, Senzhang Wang, Lifang He, Bo Li, Lihong Wang, Philip S. Yu:
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. CoRR abs/1906.04898 (2019) - [i18]Lichao Sun, Ji Wang, Philip S. Yu, Lifang He:
Not Just Cloud Privacy: Protecting Client Privacy in Teacher-Student Learning. CoRR abs/1910.08038 (2019) - 2018
- [c40]Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow:
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis. AAAI 2018: 117-124 - [c39]Xi Zhang, Lifang He, Kun Chen, Yuan Luo, Jiayu Zhou, Fei Wang:
Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease. AMIA 2018 - [c38]Lei Zheng, Yixue Wang, Lifang He, Sihong Xie, Fengjiao Wang, Philip S. Yu:
PER: A Probabilistic Attentional Model for Personalized Text Recommendations. BigData 2018: 911-920 - [c37]Lichao Sun, Lifang He, Zhipeng Huang, Bokai Cao, Congying Xia, Xiaokai Wei, Philip S. Yu:
Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks. ICBK 2018: 131-138 - [c36]Chaozhuo Li, Senzhang Wang, Lifang He, Philip S. Yu, Yanbo Liang, Zhoujun Li:
SSDMV: Semi-Supervised Deep Social Spammer Detection by Multi-view Data Fusion. ICDM 2018: 247-256 - [c35]Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang:
A Self-Organizing Tensor Architecture for Multi-view Clustering. ICDM 2018: 1007-1012 - [c34]Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu:
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. ICDM 2018: 1428-1433 - [c33]Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu:
Multi-View Fusion Through Cross-Modal Retrieval. ICIP 2018: 1977-1981 - [c32]Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu:
Multi-view Collective Tensor Decomposition for Cross-modal Hashing. ICMR 2018: 73-81 - [c31]Lifang He, Kun Chen, Wanwan Xu, Jiayu Zhou, Fei Wang:
Boosted Sparse and Low-Rank Tensor Regression. NeurIPS 2018: 1017-1026 - [c30]Fei Jiang, Lifang He, Yi Zheng, Enqiang Zhu, Jin Xu, Philip S. Yu:
On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation. SDM 2018: 324-332 - [c29]Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao, Philip S. Yu:
Learning from Multi-View Multi-Way Data via Structural Factorization Machines. WWW 2018: 1593-1602 - [i17]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Error-Robust Multi-View Clustering. CoRR abs/1801.00384 (2018) - [i16]Fei Jiang, Lifang He, Yi Zheng, Enqiang Zhu, Jin Xu, Philip S. Yu:
On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation. CoRR abs/1801.05855 (2018) - [i15]Lei Zheng, Chun-Ta Lu, Lifang He, Sihong Xie, Vahid Noroozi, He Huang, Philip S. Yu:
MARS: Memory Attention-Aware Recommender System. CoRR abs/1805.07037 (2018) - [i14]Xi Zhang, Lifang He, Kun Chen, Yuan Luo, Jiayu Zhou, Fei Wang:
Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease. CoRR abs/1805.08801 (2018) - [i13]Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin, Alex D. Leow:
Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis. CoRR abs/1806.07703 (2018) - [i12]Lichao Sun, Lifang He, Zhipeng Huang, Bokai Cao, Congying Xia, Xiaokai Wei, Philip S. Yu:
Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks. CoRR abs/1809.04110 (2018) - [i11]Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu:
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction. CoRR abs/1809.04188 (2018) - [i10]Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang:
A Self-Organizing Tensor Architecture for Multi-View Clustering. CoRR abs/1810.07874 (2018) - [i9]Lifang He, Kun Chen, Wanwan Xu, Jiayu Zhou, Fei Wang:
Boosted Sparse and Low-Rank Tensor Regression. CoRR abs/1811.01158 (2018) - 2017
- [j10]Ning Yang, Lifang He, Zheng Li, Philip S. Yu:
Reducing uncertainty of dynamic heterogeneous information networks: a fusing reconstructing approach. Data Min. Knowl. Discov. 31(3): 879-906 (2017) - [j9]Senzhang Wang, Xiaoming Zhang, Jianping Cao, Lifang He, Leon Stenneth, Philip S. Yu, Zhoujun Li, Zhiqiu Huang:
Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data. ACM Trans. Inf. Syst. 35(4): 40:1-40:30 (2017) - [c28]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Error-robust multi-view clustering. BigData 2017: 736-745 - [c27]Lichao Sun, Xiaokai Wei, Jiawei Zhang, Lifang He, Philip S. Yu, Witawas Srisa-an:
Contaminant removal for Android malware detection systems. BigData 2017: 1053-1062 - [c26]Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow, Ann B. Ragin:
Multi-view Clustering with Graph Embedding for Connectome Analysis. CIKM 2017: 127-136 - [c25]Yuqi Wang, Jiannong Cao, Lifang He, Wengen Li, Lichao Sun, Philip S. Yu:
Coupled Sparse Matrix Factorization for Response Time Prediction in Logistics Services. CIKM 2017: 939-947 - [c24]Junxing Zhu, Jiawei Zhang, Lifang He, Quanyuan Wu, Bin Zhou, Chenwei Zhang, Philip S. Yu:
Broad Learning based Multi-Source Collaborative Recommendation. CIKM 2017: 1409-1418 - [c23]Lifang He, Chun-Ta Lu, Hao Ding, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin:
Multi-way Multi-level Kernel Modeling for Neuroimaging Classification. CVPR 2017: 6846-6854 - [c22]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu:
A Broad Learning Approach for Context-Aware Mobile Application Recommendation. ICDM 2017: 955-960 - [c21]Guixiang Ma, Chun-Ta Lu, Lifang He, Philip S. Yu, Ann B. Ragin:
Multi-view Graph Embedding with Hub Detection for Brain Network Analysis. ICDM 2017: 967-972 - [c20]Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, LinLin Shen, Philip S. Yu, Ann B. Ragin:
Kernelized Support Tensor Machines. ICML 2017: 1442-1451 - [c19]Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin:
Structural Deep Brain Network Mining. KDD 2017: 475-484 - [c18]Bokai Cao, Lifang He, Xiaokai Wei, Mengqi Xing, Philip S. Yu, Heide Klumpp, Alex D. Leow:
t-BNE: Tensor-based Brain Network Embedding. SDM 2017: 189-197 - [c17]Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao, Philip S. Yu:
Multilinear Factorization Machines for Multi-Task Multi-View Learning. WSDM 2017: 701-709 - [i8]Chun-Ta Lu, Lifang He, Hao Ding, Philip S. Yu:
Learning from Multi-View Structural Data via Structural Factorization Machines. CoRR abs/1704.03037 (2017) - [i7]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu:
A Broad Learning Approach for Context-Aware Mobile Application Recommendation. CoRR abs/1709.03621 (2017) - [i6]Guixiang Ma, Chun-Ta Lu, Lifang He, Philip S. Yu, Ann B. Ragin:
Multi-view Graph Embedding with Hub Detection for Brain Network Analysis. CoRR abs/1709.03659 (2017) - [i5]Lichao Sun, Xiaokai Wei, Jiawei Zhang, Lifang He, Philip S. Yu, Witawas Srisa-an:
Contaminant Removal for Android Malware Detection Systems. CoRR abs/1711.02715 (2017) - 2016
- [j8]De-Yu Tang, Shoubin Dong, Lifang He, Yi Jiang:
Intrusive tumor growth inspired optimization algorithm for data clustering. Neural Computing and Applications 27(2): 349-374 (2016) - [c16]Weixiang Shao, Lifang He, Chun-Ta Lu, Philip S. Yu:
Online multi-view clustering with incomplete views. BigData 2016: 1012-1017 - [c15]Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu:
Online Unsupervised Multi-view Feature Selection. ICDM 2016: 1203-1208 - [c14]Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He, Philip S. Yu:
Item Recommendation for Emerging Online Businesses. IJCAI 2016: 3797-3803 - [c13]Weixiang Shao, Jiawei Zhang, Lifang He, Philip S. Yu:
Multi-source Multi-view Clustering via discrepancy penalty. IJCNN 2016: 2714-2721 - [c12]Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu:
Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. KDD 2016: 875-884 - [c11]Senzhang Wang, Lifang He, Leon Stenneth, Philip S. Yu, Zhoujun Li, Zhiqiu Huang:
Estimating Urban Traffic Congestions with Multi-sourced Data. MDM 2016: 82-91 - [c10]Guixiang Ma, Lifang He, Bokai Cao, Jiawei Zhang, Philip S. Yu, Ann B. Ragin:
Multi-graph Clustering Based on Interior-Node Topology with Applications to Brain Networks. ECML/PKDD (1) 2016: 476-492 - [c9]Jiawei Zhang, Qianyi Zhan, Lifang He, Charu C. Aggarwal, Philip S. Yu:
Trust Hole Identification in Signed Networks. ECML/PKDD (1) 2016: 697-713 - [c8]Guixiang Ma, Lifang He, Chun-Ta Lu, Philip S. Yu, Linlin Shen, Ann B. Ragin:
Spatio-Temporal Tensor Analysis for Whole-Brain fMRI Classification. SDM 2016: 819-827 - [i4]Weixiang Shao, Jiawei Zhang, Lifang He, Philip S. Yu:
Multi-Source Multi-View Clustering via Discrepancy Penalty. CoRR abs/1604.04029 (2016) - [i3]Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu:
Online Unsupervised Multi-view Feature Selection. CoRR abs/1609.08286 (2016) - [i2]Weixiang Shao, Lifang He, Chun-Ta Lu, Philip S. Yu:
Online Multi-view Clustering with Incomplete Views. CoRR abs/1611.00481 (2016) - 2015
- [j7]Xiaowei Yang, Le Han, Yan Li, Lifang He:
A bilateral-truncated-loss based robust support vector machine for classification problems. Soft Comput. 19(10): 2871-2882 (2015) - [j6]Xiaolan Liu, Tengjiao Guo, Lifang He, Xiaowei Yang:
A Low-Rank Approximation-Based Transductive Support Tensor Machine for Semisupervised Classification. IEEE Trans. Image Process. 24(6): 1825-1838 (2015) - [c7]Xiaobing Han, Yanfei Zhong, Lifang He, Philip S. Yu, Liangpei Zhang:
The Unsupervised Hierarchical Convolutional Sparse Auto-Encoder for Neuroimaging Data Classification. BIH 2015: 156-166 - [c6]Senzhang Wang, Lifang He, Leon Stenneth, Philip S. Yu, Zhoujun Li:
Citywide traffic congestion estimation with social media. SIGSPATIAL/GIS 2015: 34:1-34:10 - [c5]Weixiang Shao, Lifang He, Philip S. Yu:
Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization. PAKDD (2) 2015: 485-497 - [c4]Weixiang Shao, Lifang He, Philip S. Yu:
Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2, 1 Regularization. ECML/PKDD (1) 2015: 318-334 - 2014
- [j5]Xiaowei Yang, Liangjun Tan, Lifang He:
A robust least squares support vector machine for regression and classification with noise. Neurocomputing 140: 41-52 (2014) - [j4]Tengjiao Guo, Le Han, Lifang He, Xiaowei Yang:
A GA-based feature selection and parameter optimization for linear support higher-order tensor machine. Neurocomputing 144: 408-416 (2014) - [c3]Bokai Cao, Lifang He, Xiangnan Kong, Philip S. Yu, Zhifeng Hao, Ann B. Ragin:
Tensor-Based Multi-view Feature Selection with Applications to Brain Diseases. ICDM 2014: 40-49 - [c2]Lifang He, Hong-Han Shuai, Xiangnan Kong, Zhifeng Hao, Xiaowei Yang, Philip S. Yu:
Low-Density Cut Based Tree Decomposition for Large-Scale SVM Problems. ICDM 2014: 839-844 - [c1]Lifang He, Xiangnan Kong, Philip S. Yu, Xiaowei Yang, Ann B. Ragin, Zhifeng Hao:
DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. SDM 2014: 127-135 - [i1]Lifang He, Xiangnan Kong, Philip S. Yu, Ann B. Ragin, Zhifeng Hao, Xiaowei Yang:
DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages. CoRR abs/1407.8289 (2014) - 2013
- [j3]Xiaowei Yang, Qiaozhen Yu, Lifang He, Tengjiao Guo:
The one-against-all partition based binary tree support vector machine algorithms for multi-class classification. Neurocomputing 113: 1-7 (2013) - [j2]Lifang He, Xiaowei Yang, Zhifeng Hao:
An adaptive class pairwise dimensionality reduction algorithm. Neural Computing and Applications 23(2): 299-310 (2013) - [j1]Zhifeng Hao, Lifang He, Bingqian Chen, Xiaowei Yang:
A Linear Support Higher-Order Tensor Machine for Classification. IEEE Trans. Image Process. 22(7): 2911-2920 (2013)
Coauthor Index
[j13] [j12] [j11] [c42] [c41] [i19] [i18] [c40] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c30] [c29] [i17] [i16] [i15] [i13] [i12] [i11] [i10] [j10] [j9] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [i8] [i7] [i6] [i5] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [i4] [i3] [i2] [c7] [c6] [c5] [c4] [c3] [c2] [c1] [i1]
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