Fanhua Shang

According to our database, Fanhua Shang authored at least 120 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Arbitrary-scale Super-resolution via Deep Learning: A Comprehensive Survey.

Hongying Liu, Zekun Li, Fanhua Shang, Yuanyuan Liu, Liang Wang, Wei Feng, Radu Timofte

Inf. Fusion, February, 2024

Elastic Multi-Gradient Descent for Parallel Continual Learning.

Fan Lyu, Wei Feng, Yuepan Li, Qing Sun, Fanhua Shang, Liang Wan, Liang Wang

CoRR, 2024

Long-Tailed Learning as Multi-Objective Optimization.

Weiqi Li, Fan Lyu, Fanhua Shang, Liang Wan, Wei Feng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network.

Zekun Li, Hongying Liu, Fanhua Shang, Yuanyuan Liu, Liang Wan, Wei Feng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Subgraph-aware virtual node matching Graph Attention Network for entity alignment.

Luheng Yang, Jianrui Chen, Zhihui Wang, Fanhua Shang

Expert Syst. Appl., November, 2023

Fast and Effective: A Novel Sequential Single-Path Search for Mixed-Precision-Quantized Networks.

Qigong Sun, Xiufang Li, Licheng Jiao, Yan Ren, Fanhua Shang, Fang Liu

IEEE Trans. Cybern., October, 2023

Lightweight Super-Resolution with Self-Calibrated Convolution for Panoramic Videos.

Fanjie Shang, Hongying Liu, Wanhao Ma, Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Lijun Wang, Zhenyu Zhou

Sensors, 2023

Boosting Adversarial Transferability by Achieving Flat Local Maxima.

Zhijin Ge, Xiaosen Wang, Hongying Liu, Fanhua Shang, Yuanyuan Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization.

Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu, Zhouchen Lin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer.

Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Liang Wan, Wei Feng, Xiaosen Wang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Measuring Asymmetric Gradient Discrepancy in Parallel Continual Learning.

Fan Lyu, Qing Sun, Fanhua Shang, Liang Wan, Wei Feng

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Adaptive Non-Local Generative Adversarial Networks for Low-Dose CT Image Denoising.

Linlin Yang, Hongying Liu, Fanhua Shang, Yuanyuan Liu

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Efficient Gradient Support Pursuit With Less Hard Thresholding for Cardinality-Constrained Learning.

Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Pan Zhou, Maoguo Gong

IEEE Trans. Neural Networks Learn. Syst., 2022

Asynchronous Parallel, Sparse Approximated SVRG for High-Dimensional Machine Learning.

Fanhua Shang, Hua Huang, Jun Fan, Yuanyuan Liu, Hongying Liu, Jianhui Liu

IEEE Trans. Knowl. Data Eng., 2022

Laplacian Smoothing Stochastic ADMMs With Differential Privacy Guarantees.

Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu, Wei Feng

IEEE Trans. Inf. Forensics Secur., 2022

Global Convergence Guarantees of (A)GIST for a Family of Nonconvex Sparse Learning Problems.

Hengmin Zhang, Feng Qian, Fanhua Shang, Wenli Du, Jianjun Qian, Jian Yang

IEEE Trans. Cybern., 2022

Loopless Variance Reduced Stochastic ADMM for Equality Constrained Problems in IoT Applications.

Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu

IEEE Internet Things J., 2022

Video super-resolution based on deep learning: a comprehensive survey.

Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte

Artif. Intell. Rev., 2022

Exploring Example Influence in Continual Learning.

Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Balanced Gradient Penalty Improves Deep Long-Tailed Learning.

Dong Wang, Yicheng Liu, Liangji Fang, Fanhua Shang, Yuanyuan Liu, Hongying Liu

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

A Numerical DEs Perspective on Unfolded Linearized ADMM Networks for Inverse Problems.

Weixin An, Yingjie Yue, Yuanyuan Liu, Fanhua Shang, Hongying Liu

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

PWPROP: A Progressive Weighted Adaptive Method for Training Deep Neural Networks.

Dong Wang, Tao Xu, Huatian Zhang, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Shengmei Shen

Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots.

Yuanyuan Liu, Fanhua Shang, Weixin An, Hongying Liu, Zhouchen Lin

Proceedings of the International Conference on Machine Learning, 2022

HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks.

Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Differentially Private ADMM Algorithms for Machine Learning.

Fanhua Shang, Tao Xu, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong

IEEE Trans. Inf. Forensics Secur., 2021

Deep Fuzzy Graph Convolutional Networks for PolSAR Imagery Pixelwise Classification.

Hongying Liu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Derui Lv, Shuyuan Yang

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Graph Convolutional Networks by Architecture Search for PolSAR Image Classification.

Hongying Liu, Derong Xu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Jianhua Lu, Ri Yang

Remote. Sens., 2021

Dual space latent representation learning for unsupervised feature selection.

Ronghua Shang, Lujuan Wang, Fanhua Shang, Licheng Jiao, Yangyang Li

Pattern Recognit., 2021

Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning.

Yuanyuan Liu, Fanhua Shang, Hongying Liu, Lin Kong, Licheng Jiao, Zhouchen Lin

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Graph Convolutional Neural Networks with Geometric and Discrimination information.

Ronghua Shang, Yang Meng, Weitong Zhang, Fanhua Shang, Licheng Jiao, Shuyuan Yang

Eng. Appl. Artif. Intell., 2021

A novel recommendation scheme with multifactorial weighted matrix decomposition strategies via forgetting rule.

Jianrui Chen, Yanqing Lu, Fanhua Shang, Tingting Zhu

Eng. Appl. Artif. Intell., 2021

Learned Interpretable Residual Extragradient ISTA for Sparse Coding.

Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu

CoRR, 2021

Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration.

Qigong Sun, Xiufang Li, Fanhua Shang, Hongying Liu, Kang Yang, Licheng Jiao, Zhouchen Lin

CoRR, 2021

MWQ: Multiscale Wavelet Quantized Neural Networks.

Qigong Sun, Yan Ren, Licheng Jiao, Xiufang Li, Fanhua Shang, Fang Liu

CoRR, 2021

Effective and Fast: A Novel Sequential Single Path Search for Mixed-Precision Quantization.

Qigong Sun, Licheng Jiao, Yan Ren, Xiufang Li, Fanhua Shang, Fang Liu

CoRR, 2021

A fuzzy matrix factor recommendation method with forgetting function and user features.

Jianrui Chen, Yanqing Lu, Fanhua Shang, Yuyang Wang

Appl. Soft Comput., 2021

A Novel Learned Primal-Dual Network for Image Compressive Sensing.

Chaolong Zhang, Yuanyuan Liu, Fanhua Shang, Yangyang Li, Hongying Liu

IEEE Access, 2021

Efficient Asynchronous Semi-Stochastic Block Coordinate Descent Methods for Large-Scale SVD.

Fanhua Shang, Zhihui Zhang, Yuanyuan Liu, Hongying Liu, Jing Xu

IEEE Access, 2021

Principal component analysis in the stochastic differential privacy model.

Fanhua Shang, Zhihui Zhang, Tao Xu, Yuanyuan Liu, Hongying Liu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Progressive Semantic Matching for Video-Text Retrieval.

Hongying Liu, Ruyi Luo, Fanhua Shang, Mantang Niu, Yuanyuan Liu

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning.

Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling.

Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding.

Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Semi-Supervised Graph Regularized Deep NMF With Bi-Orthogonal Constraints for Data Representation.

Yang Meng, Ronghua Shang, Fanhua Shang, Licheng Jiao, Shuyuan Yang, Rustam Stolkin

IEEE Trans. Neural Networks Learn. Syst., 2020

Sparse Manifold-Regularized Neural Networks for Polarimetric SAR Terrain Classification.

Hongying Liu, Fanhua Shang, Shuyuan Yang, Maoguo Gong, Tianwen Zhu, Licheng Jiao

IEEE Trans. Neural Networks Learn. Syst., 2020

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao

IEEE Trans. Knowl. Data Eng., 2020

Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications.

Fanhua Shang, Bingkun Wei, Yuanyuan Liu, Hongying Liu, Shuang Wang, Licheng Jiao

Sensors, 2020

Semantic Segmentation for SAR Image Based on Texture Complexity Analysis and Key Superpixels.

Ronghua Shang, Pei Peng, Fanhua Shang, Licheng Jiao, Yifei Shen, Rustam Stolkin

Remote. Sens., 2020

Semi-Supervised Deep Metric Learning Networks for Classification of Polarimetric SAR Data.

Hongying Liu, Ruyi Luo, Fanhua Shang, Xuechun Meng, Shuiping Gou, Biao Hou

Remote. Sens., 2020

Sparse and low-redundant subspace learning-based dual-graph regularized robust feature selection.

Ronghua Shang, Kaiming Xu, Fanhua Shang, Licheng Jiao

Knowl. Based Syst., 2020

Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks.

Pengtao Xu, Jian Cao, Fanhua Shang, Wenyu Sun, Pu Li

CoRR, 2020

Boosting Gradient for White-Box Adversarial Attacks.

Hongying Liu, Zhenyu Zhou, Fanhua Shang, Xiaoyu Qi, Yuanyuan Liu, Licheng Jiao

CoRR, 2020

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution.

Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang

CoRR, 2020

Video Super Resolution Based on Deep Learning: A comprehensive survey.

Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang, Yuanyuan Liu

CoRR, 2020

A Unified Weight Learning and Low-Rank Regression Model for Robust Face Recognition.

Miaohua Zhang, Yongsheng Gao, Fanhua Shang

CoRR, 2020

Data Augmentation Imbalance For Imbalanced Attribute Classification.

Xiaying Bai, Yang Hu, Pan Zhou, Fanhua Shang, Shengmei Shen

CoRR, 2020

Deep Residual-Dense Lattice Network for Speech Enhancement.

Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao, Jun Zhou, Kuldip K. Paliwal, Fanhua Shang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

LRR for Subspace Segmentation via Tractable Schatten- $p$ Norm Minimization and Factorization.

Hengmin Zhang, Jian Yang, Fanhua Shang, Chen Gong, Zhenyu Zhang

IEEE Trans. Cybern., 2019

Local discriminative based sparse subspace learning for feature selection.

Ronghua Shang, Yang Meng, Wenbing Wang, Fanhua Shang, Licheng Jiao

Pattern Recognit., 2019

Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization.

Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Jiacheng Zhuo

CoRR, 2019

CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.

Hongying Liu, Xiongjie Shen, Fanhua Shang, Fei Wang

CoRR, 2019

Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1.

Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao

CoRR, 2019

CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.

Hongying Liu, Xiongjie Shen, Fanhua Shang, Feihang Ge, Fei Wang

Proceedings of the Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy, 2019

Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor.

Yuanyuan Liu, Fanhua Shang, Licheng Jiao

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks.

Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

signADAM++: Learning Confidences for Deep Neural Networks.

Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Efficient Parallel Stochastic Variance Reduction Algorithms for Large-Scale SVD.

Fanhua Shang, Zhihui Zhang, Yuying An, Yang Hu, Hongying Liu

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

A Novel Deep Framework for Change Detection of Multi-source Heterogeneous Images.

Hongying Liu, Zhongshu Wang, Fanhua Shang, Mingyang Zhang, Maoguo Gong, Feihang Ge, Licheng Jiao

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

A Stochastic Variance Reduced Extragradient Method for Sparse Machine Learning Problems.

Lin Kong, Xiaying Bai, Yang Hu, Fanhua Shang, Yuanyuan Liu, Hongying Liu

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Loopless Semi-Stochastic Gradient Descent with Less Hard Thresholding for Sparse Learning.

Xiangyang Liu, Bingkun Wei, Fanhua Shang, Hongying Liu

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Direct Acceleration of SAGA using Sampled Negative Momentum.

Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1, +1}.

Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Fuzzy Double Trace Norm Minimization for Recommendation Systems.

Fanhua Shang, Yuanyuan Liu, James Cheng, Da Yan

IEEE Trans. Fuzzy Syst., 2018

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications.

Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Semi-Supervised Tensorial Locally Linear Embedding for Feature Extraction Using PolSAR Data.

Hongying Liu, Zhi Wang, Fanhua Shang, Shuyuan Yang, Shuiping Gou, Licheng Jiao

IEEE J. Sel. Top. Signal Process., 2018

A Unified Approximation Framework for Deep Neural Networks.

Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

CoRR, 2018

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao

CoRR, 2018

A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates.

Kaiwen Zhou, Fanhua Shang, James Cheng

Proceedings of the 35th International Conference on Machine Learning, 2018

Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization.

Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

ASVRG: Accelerated Proximal SVRG.

Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin

Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017

LFTF: A Framework for Efficient Tensor Analytics at Scale.

Fan Yang, Fanhua Shang, Yuzhen Huang, James Cheng, Jinfeng Li, Yunjian Zhao, Ruihao Zhao

Proc. VLDB Endow., 2017

Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning.

Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo

CoRR, 2017

Variance Reduced Stochastic Gradient Descent with Sufficient Decrease.

Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida

CoRR, 2017

Larger is Better: The Effect of Learning Rates Enjoyed by Stochastic Optimization with Progressive Variance Reduction.

Fanhua Shang

CoRR, 2017

Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds.

Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Accelerated Variance Reduced Stochastic ADMM.

Yuanyuan Liu, Fanhua Shang, James Cheng

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition.

Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng

IEEE Trans. Neural Networks Learn. Syst., 2016

Unified Scalable Equivalent Formulations for Schatten Quasi-Norms.

Fanhua Shang, Yuanyuan Liu, James Cheng

CoRR, 2016

Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization.

Fanhua Shang, Yuanyuan Liu, James Cheng

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization.

Fanhua Shang, Yuanyuan Liu, James Cheng

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, Hong Cheng

IEEE Trans. Cybern., 2015

Robust bilinear factorization with missing and grossly corrupted observations.

Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng

Inf. Sci., 2015

Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning.

Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng

CoRR, 2015

2014

Double linear regressions for single labeled image per person face recognition.

Fei Yin, Licheng Jiao, Fanhua Shang, Lin Xiong, Shasha Mao

Pattern Recognit., 2014

Maximum margin multiple-instance feature weighting.

Jing Chai, Hongtao Chen, Lixia Huang, Fanhua Shang

Pattern Recognit., 2014

Sparse regularization discriminant analysis for face recognition.

Fei Yin, Licheng Jiao, Fanhua Shang, Lin Xiong, Xiaodong Wang

Neurocomputing, 2014

Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations.

Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng

CoRR, 2014

Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds.

Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion.

Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, Hanghang Tong

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion.

Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization.

Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Robust Principal Component Analysis with Missing Data.

Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Generalized Higher-Order Tensor Decomposition via Parallel ADMM.

Fanhua Shang, Yuanyuan Liu, James Cheng

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

An Efficient Matrix Factorization Method for Tensor Completion.

Yuanyuan Liu, Fanhua Shang

IEEE Signal Process. Lett., 2013

Sparse coding and classifier ensemble based multi-instance learning for image categorization.

Xiangfa Song, Licheng Jiao, Shuyuan Yang, Xiangrong Zhang, Fanhua Shang

Signal Process., 2013

Semi-supervised learning with nuclear norm regularization.

Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Hanghang Tong

Pattern Recognit., 2013

An efficient matrix factorization based low-rank representation for subspace clustering.

Yuanyuan Liu, Licheng Jiao, Fanhua Shang

Pattern Recognit., 2013

A fast tri-factorization method for low-rank matrix recovery and completion.

Yuanyuan Liu, Licheng Jiao, Fanhua Shang

Pattern Recognit., 2013

An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion.

Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Fei Yin, Fang Liu

Neural Networks, 2013

Fast Fisher Sparsity Preserving Projections.

Fei Yin, Licheng Jiao, Fanhua Shang, Shuang Wang, Biao Hou

Neural Comput. Appl., 2013

2012

An evidential reasoning based classification algorithm and its application for face recognition with class noise.

Xiaodong Wang, Fang Liu, Licheng Jiao, Zhiguo Zhou, Jingjing Yu, Bing Li, Jianrui Chen, Jiao Wu, Fanhua Shang

Pattern Recognit., 2012

Graph dual regularization non-negative matrix factorization for co-clustering.

Fanhua Shang, Licheng Jiao, Fei Wang

Pattern Recognit., 2012

Fast affinity propagation clustering: A multilevel approach.

Fanhua Shang, Licheng Jiao, Jiarong Shi, Fei Wang, Maoguo Gong

Pattern Recognit., 2012

Fast semi-supervised clustering with enhanced spectral embedding.

Licheng Jiao, Fanhua Shang, Fei Wang, Yuanyuan Liu

Pattern Recognit., 2012

Integrating Spectral Kernel Learning and Constraints in Semi-Supervised Classification.

Fanhua Shang, Licheng Jiao, Yuanyuan Liu

Neural Process. Lett., 2012

Semi-supervised learning with mixed knowledge information.

Fanhua Shang, Licheng Jiao, Fei Wang

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Learning spectral embedding via iterative eigenvalue thresholding.

Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Fei Wang

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Robust Positive semidefinite L-Isomap Ensemble.

Fanhua Shang, Licheng Jiao, Jiarong Shi, Jing Chai

Pattern Recognit. Lett., 2011

Fast density-weighted low-rank approximation spectral clustering.

Fanhua Shang, Licheng Jiao, Jiarong Shi, Maoguo Gong, Ronghua Shang

Data Min. Knowl. Discov., 2011

Learning Spectral Embedding for Semi-supervised Clustering.

Fanhua Shang, Yuanyuan Liu, Fei Wang

Proceedings of the 11th IEEE International Conference on Data Mining, 2011