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2020 – today
- 2024
[j57]Luheng Yang
, Jianrui Chen, Zhihui Wang, Fanhua Shang:
Relation mapping based on higher-order graph convolutional network for entity alignment. Eng. Appl. Artif. Intell. 133: 108009 (2024)- [j56]Hongying Liu, Wanhao Ma, Zhubo Ruan, Chaowei Fang, Fanhua Shang, Yuanyuan Liu, Lijun Wang, Chaoli Wang, Dongmei Jiang:
A single frame and multi-frame joint network for 360-degree panorama video super-resolution. Eng. Appl. Artif. Intell. 134: 108601 (2024) - [j55]Deguang Chen, Jianrui Chen, Luheng Yang, Fanhua Shang:
Mix-tower: Light visual question answering framework based on exclusive self-attention mechanism. Neurocomputing 587: 127686 (2024) - [j54]Hongying Liu, Zekun Li, Fanhua Shang, Yuanyuan Liu, Liang Wang, Wei Feng, Radu Timofte:
Arbitrary-scale Super-resolution via Deep Learning: A Comprehensive Survey. Inf. Fusion 102: 102015 (2024) - [j53]Hongying Liu, Linlin Yang, Longge Zhang, Fanhua Shang, Yuanyuan Liu, Lijun Wang:
Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering. Sensors 24(11): 3659 (2024) - [c45]Weiqi Li, Fan Lyu, Fanhua Shang, Liang Wan, Wei Feng:
Long-Tailed Learning as Multi-Objective Optimization. AAAI 2024: 3190-3198 - [c44]Zekun Li, Hongying Liu, Fanhua Shang, Yuanyuan Liu, Liang Wan, Wei Feng:
SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network. AAAI 2024: 3288-3296 - [i45]Fan Lyu, Wei Feng, Yuepan Li, Qing Sun, Fanhua Shang, Liang Wan, Liang Wang:
Elastic Multi-Gradient Descent for Parallel Continual Learning. CoRR abs/2401.01054 (2024) - [i44]Fan Lyu, Daofeng Liu, Linglan Zhao, Zhang Zhang, Fanhua Shang, Fuyuan Hu, Wei Feng, Liang Wang:
Overcoming Domain Drift in Online Continual Learning. CoRR abs/2405.09133 (2024) - [i43]Ziqi Shi, Fan Lyu, Ye Liu, Fanhua Shang, Fuyuan Hu, Wei Feng, Zhang Zhang, Liang Wang:
Controllable Continual Test-Time Adaptation. CoRR abs/2405.14602 (2024) - [i42]Tianling Liu, Hongying Liu, Fanhua Shang, Lequan Yu, Tong Han, Liang Wan:
Completed Feature Disentanglement Learning for Multimodal MRIs Analysis. CoRR abs/2407.04916 (2024) - [i41]Yuepan Li, Fan Lyu, Yuyang Li, Wei Feng, Guangcan Liu, Fanhua Shang:
Towards stable training of parallel continual learning. CoRR abs/2407.08214 (2024) - [i40]Yifei Gao, Jie Ou, Lei Wang, Fanhua Shang, Jaji Wu, Jun Cheng:
Compensate Quantization Errors+: Quantized Models Are Inquisitive Learners. CoRR abs/2407.15508 (2024) - [i39]Tongkai Shi, Lianyu Hu, Fanhua Shang, Jichao Feng, Peidong Liu, Wei Feng:
Pose-Guided Fine-Grained Sign Language Video Generation. CoRR abs/2409.16709 (2024) - 2023
- [j52]Luheng Yang, Jianrui Chen, Zhihui Wang, Fanhua Shang:
Subgraph-aware virtual node matching Graph Attention Network for entity alignment. Expert Syst. Appl. 231: 120694 (2023) - [j51]Fanjie Shang, Hongying Liu, Wanhao Ma, Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Lijun Wang, Zhenyu Zhou:
Lightweight Super-Resolution with Self-Calibrated Convolution for Panoramic Videos. Sensors 23(1): 392 (2023) - [j50]Qigong Sun, Xiufang Li, Licheng Jiao, Yan Ren, Fanhua Shang, Fang Liu:
Fast and Effective: A Novel Sequential Single-Path Search for Mixed-Precision-Quantized Networks. IEEE Trans. Cybern. 53(10): 6187-6199 (2023) - [c43]Linlin Yang, Hongying Liu, Fanhua Shang, Yuanyuan Liu:
Adaptive Non-Local Generative Adversarial Networks for Low-Dose CT Image Denoising. ICASSP 2023: 1-5 - [c42]Fan Lyu, Qing Sun, Fanhua Shang, Liang Wan, Wei Feng:
Measuring Asymmetric Gradient Discrepancy in Parallel Continual Learning. ICCV 2023: 11377-11386 - [c41]Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Liang Wan, Wei Feng, Xiaosen Wang:
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer. ACM Multimedia 2023: 4440-4449 - [c40]Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu, Zhouchen Lin:
A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization. NeurIPS 2023 - [c39]Zhijin Ge, Xiaosen Wang, Hongying Liu, Fanhua Shang, Yuanyuan Liu:
Boosting Adversarial Transferability by Achieving Flat Local Maxima. NeurIPS 2023 - [i38]Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Xiaosen Wang:
Boosting Adversarial Transferability by Achieving Flat Local Maxima. CoRR abs/2306.05225 (2023) - [i37]Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Liang Wan, Wei Feng, Xiaosen Wang:
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer. CoRR abs/2308.10601 (2023) - [i36]Weiqi Li, Fan Lyu, Fanhua Shang, Liang Wan, Wei Feng:
Long-Tailed Learning as Multi-Objective Optimization. CoRR abs/2310.20490 (2023) - 2022
- [j49]Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte:
Video super-resolution based on deep learning: a comprehensive survey. Artif. Intell. Rev. 55(8): 5981-6035 (2022) - [j48]Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu:
Loopless Variance Reduced Stochastic ADMM for Equality Constrained Problems in IoT Applications. IEEE Internet Things J. 9(3): 2293-2303 (2022) - [j47]Hengmin Zhang, Feng Qian, Fanhua Shang, Wenli Du, Jianjun Qian, Jian Yang:
Global Convergence Guarantees of (A)GIST for a Family of Nonconvex Sparse Learning Problems. IEEE Trans. Cybern. 52(5): 3276-3288 (2022) - [j46]Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu, Wei Feng:
Laplacian Smoothing Stochastic ADMMs With Differential Privacy Guarantees. IEEE Trans. Inf. Forensics Secur. 17: 1814-1826 (2022) - [j45]Fanhua Shang, Hua Huang, Jun Fan, Yuanyuan Liu, Hongying Liu, Jianhui Liu:
Asynchronous Parallel, Sparse Approximated SVRG for High-Dimensional Machine Learning. IEEE Trans. Knowl. Data Eng. 34(12): 5636-5648 (2022) - [j44]Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Pan Zhou, Maoguo Gong:
Efficient Gradient Support Pursuit With Less Hard Thresholding for Cardinality-Constrained Learning. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7806-7817 (2022) - [c38]Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks. AAAI 2022: 7220-7228 - [c37]Yuanyuan Liu, Fanhua Shang, Weixin An, Hongying Liu, Zhouchen Lin:
Kill a Bird with Two Stones: Closing the Convergence Gaps in Non-Strongly Convex Optimization by Directly Accelerated SVRG with Double Compensation and Snapshots. ICML 2022: 14008-14035 - [c36]Dong Wang, Tao Xu, Huatian Zhang, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Shengmei Shen:
PWPROP: A Progressive Weighted Adaptive Method for Training Deep Neural Networks. ICTAI 2022: 508-515 - [c35]Weixin An, Yingjie Yue, Yuanyuan Liu, Fanhua Shang, Hongying Liu:
A Numerical DEs Perspective on Unfolded Linearized ADMM Networks for Inverse Problems. ACM Multimedia 2022: 5065-5073 - [c34]Dong Wang, Yicheng Liu, Liangji Fang, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
Balanced Gradient Penalty Improves Deep Long-Tailed Learning. ACM Multimedia 2022: 5093-5101 - [c33]Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan:
Exploring Example Influence in Continual Learning. NeurIPS 2022 - [i35]Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan:
Exploring Example Influence in Continual Learning. CoRR abs/2209.12241 (2022) - 2021
- [j43]Chaolong Zhang, Yuanyuan Liu, Fanhua Shang, Yangyang Li, Hongying Liu:
A Novel Learned Primal-Dual Network for Image Compressive Sensing. IEEE Access 9: 26041-26050 (2021) - [j42]Fanhua Shang, Zhihui Zhang, Yuanyuan Liu, Hongying Liu, Jing Xu:
Efficient Asynchronous Semi-Stochastic Block Coordinate Descent Methods for Large-Scale SVD. IEEE Access 9: 126159-126171 (2021) - [j41]Jianrui Chen, Yanqing Lu, Fanhua Shang, Yuyang Wang:
A fuzzy matrix factor recommendation method with forgetting function and user features. Appl. Soft Comput. 100: 106910 (2021) - [j40]Jianrui Chen, Yanqing Lu, Fanhua Shang, Tingting Zhu:
A novel recommendation scheme with multifactorial weighted matrix decomposition strategies via forgetting rule. Eng. Appl. Artif. Intell. 101: 104191 (2021) - [j39]Ronghua Shang, Yang Meng, Weitong Zhang, Fanhua Shang, Licheng Jiao, Shuyuan Yang:
Graph Convolutional Neural Networks with Geometric and Discrimination information. Eng. Appl. Artif. Intell. 104: 104364 (2021) - [j38]Yuanyuan Liu, Fanhua Shang, Hongying Liu, Lin Kong, Licheng Jiao, Zhouchen Lin:
Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4242-4255 (2021) - [j37]Ronghua Shang, Lujuan Wang, Fanhua Shang, Licheng Jiao, Yangyang Li:
Dual space latent representation learning for unsupervised feature selection. Pattern Recognit. 114: 107873 (2021) - [j36]Hongying Liu, Derong Xu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Jianhua Lu, Ri Yang:
Graph Convolutional Networks by Architecture Search for PolSAR Image Classification. Remote. Sens. 13(7): 1404 (2021) - [j35]Hongying Liu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Derui Lv, Shuyuan Yang:
Deep Fuzzy Graph Convolutional Networks for PolSAR Imagery Pixelwise Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 504-514 (2021) - [j34]Fanhua Shang, Tao Xu, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong:
Differentially Private ADMM Algorithms for Machine Learning. IEEE Trans. Inf. Forensics Secur. 16: 4733-4745 (2021) - [c32]Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu:
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling. AAAI 2021: 2127-2135 - [c31]Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin:
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding. AAAI 2021: 8501-8509 - [c30]Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. IJCAI 2021: 2556-2562 - [c29]Hongying Liu, Ruyi Luo, Fanhua Shang, Mantang Niu, Yuanyuan Liu:
Progressive Semantic Matching for Video-Text Retrieval. ACM Multimedia 2021: 5083-5091 - [c28]Fanhua Shang, Zhihui Zhang, Tao Xu, Yuanyuan Liu, Hongying Liu:
Principal component analysis in the stochastic differential privacy model. UAI 2021: 1110-1119 - [i34]Qigong Sun, Licheng Jiao, Yan Ren, Xiufang Li, Fanhua Shang, Fang Liu:
Effective and Fast: A Novel Sequential Single Path Search for Mixed-Precision Quantization. CoRR abs/2103.02904 (2021) - [i33]Qigong Sun, Yan Ren, Licheng Jiao, Xiufang Li, Fanhua Shang, Fang Liu:
MWQ: Multiscale Wavelet Quantized Neural Networks. CoRR abs/2103.05363 (2021) - [i32]Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu:
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling. CoRR abs/2103.11744 (2021) - [i31]Qigong Sun, Xiufang Li, Fanhua Shang, Hongying Liu, Kang Yang, Licheng Jiao, Zhouchen Lin:
Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration. CoRR abs/2106.09886 (2021) - [i30]Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
Learned Interpretable Residual Extragradient ISTA for Sparse Coding. CoRR abs/2106.11970 (2021) - [i29]Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. CoRR abs/2106.12300 (2021) - 2020
- [j33]Ronghua Shang, Kaiming Xu, Fanhua Shang, Licheng Jiao:
Sparse and low-redundant subspace learning-based dual-graph regularized robust feature selection. Knowl. Based Syst. 187 (2020) - [j32]Hongying Liu, Ruyi Luo, Fanhua Shang, Xuechun Meng, Shuiping Gou, Biao Hou:
Semi-Supervised Deep Metric Learning Networks for Classification of Polarimetric SAR Data. Remote. Sens. 12(10): 1593 (2020) - [j31]Ronghua Shang, Pei Peng, Fanhua Shang, Licheng Jiao, Yifei Shen, Rustam Stolkin:
Semantic Segmentation for SAR Image Based on Texture Complexity Analysis and Key Superpixels. Remote. Sens. 12(13): 2141 (2020) - [j30]Fanhua Shang, Bingkun Wei, Yuanyuan Liu, Hongying Liu, Shuang Wang, Licheng Jiao:
Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications. Sensors 20(17): 4902 (2020) - [j29]Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - [j28]Hongying Liu, Fanhua Shang, Shuyuan Yang, Maoguo Gong, Tianwen Zhu, Licheng Jiao:
Sparse Manifold-Regularized Neural Networks for Polarimetric SAR Terrain Classification. IEEE Trans. Neural Networks Learn. Syst. 31(8): 3007-3016 (2020) - [j27]Yang Meng, Ronghua Shang, Fanhua Shang, Licheng Jiao, Shuyuan Yang, Rustam Stolkin:
Semi-Supervised Graph Regularized Deep NMF With Bi-Orthogonal Constraints for Data Representation. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3245-3258 (2020) - [c27]Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao, Jun Zhou, Kuldip K. Paliwal, Fanhua Shang:
Deep Residual-Dense Lattice Network for Speech Enhancement. AAAI 2020: 8552-8559 - [i28]Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao, Jun Zhou, Kuldip K. Paliwal, Fanhua Shang:
Deep Residual-Dense Lattice Network for Speech Enhancement. CoRR abs/2002.12794 (2020) - [i27]Xiaying Bai, Yang Hu, Pan Zhou, Fanhua Shang, Shengmei Shen:
Data Augmentation Imbalance For Imbalanced Attribute Classification. CoRR abs/2004.13628 (2020) - [i26]Miaohua Zhang, Yongsheng Gao, Fanhua Shang:
A Unified Weight Learning and Low-Rank Regression Model for Robust Face Recognition. CoRR abs/2005.04619 (2020) - [i25]Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang, Yuanyuan Liu:
Video Super Resolution Based on Deep Learning: A comprehensive survey. CoRR abs/2007.12928 (2020) - [i24]Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang:
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution. CoRR abs/2008.10320 (2020) - [i23]Hongying Liu, Zhenyu Zhou, Fanhua Shang, Xiaoyu Qi, Yuanyuan Liu, Licheng Jiao:
Boosting Gradient for White-Box Adversarial Attacks. CoRR abs/2010.10712 (2020) - [i22]Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong:
Differentially Private ADMM Algorithms for Machine Learning. CoRR abs/2011.00164 (2020) - [i21]Pengtao Xu, Jian Cao, Fanhua Shang, Wenyu Sun, Pu Li:
Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks. CoRR abs/2011.14356 (2020)
2010 – 2019
- 2019
- [j26]Ronghua Shang, Yang Meng, Wenbing Wang, Fanhua Shang, Licheng Jiao:
Local discriminative based sparse subspace learning for feature selection. Pattern Recognit. 92: 219-230 (2019) - [j25]Hengmin Zhang, Jian Yang, Fanhua Shang, Chen Gong, Zhenyu Zhang:
LRR for Subspace Segmentation via Tractable Schatten- $p$ Norm Minimization and Factorization. IEEE Trans. Cybern. 49(5): 1722-1734 (2019) - [c26]Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao:
Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1, +1}. AAAI 2019: 5024-5032 - [c25]Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo:
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS 2019: 1602-1610 - [c24]Xiangyang Liu, Bingkun Wei, Fanhua Shang, Hongying Liu:
Loopless Semi-Stochastic Gradient Descent with Less Hard Thresholding for Sparse Learning. CIKM 2019: 881-890 - [c23]Lin Kong, Xiaying Bai, Yang Hu, Fanhua Shang, Yuanyuan Liu, Hongying Liu:
A Stochastic Variance Reduced Extragradient Method for Sparse Machine Learning Problems. ICDM Workshops 2019: 155-164 - [c22]Hongying Liu, Zhongshu Wang, Fanhua Shang, Mingyang Zhang, Maoguo Gong, Feihang Ge, Licheng Jiao:
A Novel Deep Framework for Change Detection of Multi-source Heterogeneous Images. ICDM Workshops 2019: 165-171 - [c21]Fanhua Shang, Zhihui Zhang, Yuying An, Yang Hu, Hongying Liu:
Efficient Parallel Stochastic Variance Reduction Algorithms for Large-Scale SVD. ICDM Workshops 2019: 172-179 - [c20]Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao:
signADAM++: Learning Confidences for Deep Neural Networks. ICDM Workshops 2019: 186-195 - [c19]Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu:
A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks. ICTAI 2019: 376-383 - [c18]Yuanyuan Liu, Fanhua Shang, Licheng Jiao:
Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor. IJCAI 2019: 3045-3051 - [c17]Hongying Liu, Xiongjie Shen, Fanhua Shang, Feihang Ge, Fei Wang:
CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation. MBIA/MFCA@MICCAI 2019: 102-111 - [i20]Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao:
Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1. CoRR abs/1905.13389 (2019) - [i19]Hongying Liu, Xiongjie Shen, Fanhua Shang, Fei Wang:
CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation. CoRR abs/1907.07677 (2019) - [i18]Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao:
signADAM: Learning Confidences for Deep Neural Networks. CoRR abs/1907.09008 (2019) - [i17]Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Jiacheng Zhuo:
Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization. CoRR abs/1912.00858 (2019) - 2018
- [j24]Hongying Liu, Zhi Wang, Fanhua Shang, Shuyuan Yang, Shuiping Gou, Licheng Jiao:
Semi-Supervised Tensorial Locally Linear Embedding for Feature Extraction Using PolSAR Data. IEEE J. Sel. Top. Signal Process. 12(6): 1476-1490 (2018) - [j23]Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin:
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 40(9): 2066-2080 (2018) - [j22]Fanhua Shang, Yuanyuan Liu, James Cheng, Da Yan:
Fuzzy Double Trace Norm Minimization for Recommendation Systems. IEEE Trans. Fuzzy Syst. 26(4): 2039-2049 (2018) - [c16]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. ACML 2018: 815-830 - [c15]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS 2018: 1027-1036 - [c14]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. ICML 2018: 5975-5984 - [i16]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i15]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR abs/1802.09933 (2018) - [i14]Fanhua Shang, Yuanyuan Liu, James Cheng:
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. CoRR abs/1803.00420 (2018) - [i13]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. CoRR abs/1806.11027 (2018) - [i12]Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu:
A Unified Approximation Framework for Deep Neural Networks. CoRR abs/1807.10119 (2018) - [i11]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. CoRR abs/1810.03105 (2018) - [i10]Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin:
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. CoRR abs/1810.05186 (2018) - 2017
- [j21]Fan Yang, Fanhua Shang, Yuzhen Huang, James Cheng, Jinfeng Li, Yunjian Zhao, Ruihao Zhao:
LFTF: A Framework for Efficient Tensor Analytics at Scale. Proc. VLDB Endow. 10(7): 745-756 (2017) - [c13]Yuanyuan Liu, Fanhua Shang, James Cheng:
Accelerated Variance Reduced Stochastic ADMM. AAAI 2017: 2287-2293 - [c12]Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao:
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. NIPS 2017: 4868-4877 - [i9]Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. CoRR abs/1703.06807 (2017) - [i8]Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo:
Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. CoRR abs/1703.07948 (2017) - [i7]Fanhua Shang:
Larger is Better: The Effect of Learning Rates Enjoyed by Stochastic Optimization with Progressive Variance Reduction. CoRR abs/1704.04966 (2017) - [i6]Yuanyuan Liu, Fanhua Shang, James Cheng:
Accelerated Variance Reduced Stochastic ADMM. CoRR abs/1707.03190 (2017) - 2016
- [j20]Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng:
Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition. IEEE Trans. Neural Networks Learn. Syst. 27(12): 2551-2563 (2016) - [c11]Fanhua Shang, Yuanyuan Liu, James Cheng:
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. AAAI 2016: 2016-2022 - [c10]Fanhua Shang, Yuanyuan Liu, James Cheng:
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. AISTATS 2016: 620-629 - [i5]Fanhua Shang, Yuanyuan Liu, James Cheng:
Unified Scalable Equivalent Formulations for Schatten Quasi-Norms. CoRR abs/1606.00668 (2016) - [i4]Fanhua Shang, Yuanyuan Liu, James Cheng:
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. CoRR abs/1606.01245 (2016) - 2015
- [j19]Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng:
Robust bilinear factorization with missing and grossly corrupted observations. Inf. Sci. 307: 53-72 (2015) - [j18]Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, Hong Cheng:
Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data. IEEE Trans. Cybern. 45(11): 2437-2448 (2015) - [i3]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning. CoRR abs/1512.08120 (2015) - 2014
- [j17]Fei Yin, Licheng Jiao, Fanhua Shang, Lin Xiong, Xiaodong Wang:
Sparse regularization discriminant analysis for face recognition. Neurocomputing 128: 341-362 (2014) - [j16]Fei Yin, Licheng Jiao, Fanhua Shang, Lin Xiong, Shasha Mao:
Double linear regressions for single labeled image per person face recognition. Pattern Recognit. 47(4): 1547-1558 (2014) - [j15]Jing Chai, Hongtao Chen, Lixia Huang, Fanhua Shang:
Maximum margin multiple-instance feature weighting. Pattern Recognit. 47(6): 2091-2103 (2014) - [c9]Fanhua Shang, Yuanyuan Liu, James Cheng:
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. AAAI 2014: 1279-1285 - [c8]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Robust Principal Component Analysis with Missing Data. CIKM 2014: 1149-1158 - [c7]Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng:
Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization. ICDM 2014: 965-970 - [c6]Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng:
Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. NIPS 2014: 1763-1771 - [c5]Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, Hanghang Tong:
Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. SDM 2014: 866-874 - [c4]Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng:
Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. UAI 2014: 515-524 - [i2]Fanhua Shang, Yuanyuan Liu, James Cheng:
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. CoRR abs/1407.1399 (2014) - [i1]Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng:
Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations. CoRR abs/1409.1062 (2014) - 2013
- [j14]Fei Yin, Licheng Jiao, Fanhua Shang, Shuang Wang, Biao Hou:
Fast Fisher Sparsity Preserving Projections. Neural Comput. Appl. 23(3-4): 691-705 (2013) - [j13]Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Fei Yin, Fang Liu:
An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion. Neural Networks 48: 8-18 (2013) - [j12]Yuanyuan Liu, Licheng Jiao, Fanhua Shang:
A fast tri-factorization method for low-rank matrix recovery and completion. Pattern Recognit. 46(1): 163-173 (2013) - [j11]Yuanyuan Liu, Licheng Jiao, Fanhua Shang:
An efficient matrix factorization based low-rank representation for subspace clustering. Pattern Recognit. 46(1): 284-292 (2013) - [j10]Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Hanghang Tong:
Semi-supervised learning with nuclear norm regularization. Pattern Recognit. 46(8): 2323-2336 (2013) - [j9]Xiangfa Song, Licheng Jiao, Shuyuan Yang, Xiangrong Zhang, Fanhua Shang:
Sparse coding and classifier ensemble based multi-instance learning for image categorization. Signal Process. 93(1): 1-11 (2013) - [j8]Yuanyuan Liu, Fanhua Shang:
An Efficient Matrix Factorization Method for Tensor Completion. IEEE Signal Process. Lett. 20(4): 307-310 (2013) - 2012
- [j7]Fanhua Shang, Licheng Jiao, Yuanyuan Liu:
Integrating Spectral Kernel Learning and Constraints in Semi-Supervised Classification. Neural Process. Lett. 36(2): 101-115 (2012) - [j6]Fanhua Shang, Licheng Jiao, Jiarong Shi, Fei Wang, Maoguo Gong:
Fast affinity propagation clustering: A multilevel approach. Pattern Recognit. 45(1): 474-486 (2012) - [j5]Fanhua Shang, Licheng Jiao, Fei Wang:
Graph dual regularization non-negative matrix factorization for co-clustering. Pattern Recognit. 45(6): 2237-2250 (2012) - [j4]Xiaodong Wang, Fang Liu, Licheng Jiao, Zhiguo Zhou, Jingjing Yu, Bing Li, Jianrui Chen, Jiao Wu, Fanhua Shang:
An evidential reasoning based classification algorithm and its application for face recognition with class noise. Pattern Recognit. 45(12): 4117-4128 (2012) - [j3]Licheng Jiao, Fanhua Shang, Fei Wang, Yuanyuan Liu:
Fast semi-supervised clustering with enhanced spectral embedding. Pattern Recognit. 45(12): 4358-4369 (2012) - [c3]Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Fei Wang:
Learning spectral embedding via iterative eigenvalue thresholding. CIKM 2012: 1507-1511 - [c2]Fanhua Shang, Licheng Jiao, Fei Wang:
Semi-supervised learning with mixed knowledge information. KDD 2012: 732-740 - 2011
- [j2]Fanhua Shang, Licheng Jiao, Jiarong Shi, Maoguo Gong, Ronghua Shang:
Fast density-weighted low-rank approximation spectral clustering. Data Min. Knowl. Discov. 23(2): 345-378 (2011) - [j1]Fanhua Shang, Licheng Jiao, Jiarong Shi, Jing Chai:
Robust Positive semidefinite L-Isomap Ensemble. Pattern Recognit. Lett. 32(4): 640-649 (2011) - [c1]Fanhua Shang, Yuanyuan Liu, Fei Wang:
Learning Spectral Embedding for Semi-supervised Clustering. ICDM 2011: 597-606
Coauthor Index
[j56] [j54] [j53] [c44] [i42] [j51] [c43] [c41] [c40] [c39] [i38] [i37] [j49] [j48] [j46] [j45] [j44] [c38] [c37] [c36] [c35] [c34] [j43] [j42] [j38] [j36] [j35] [j34] [c32] [c31] [c30] [c29] [c28] [i32] [i31] [i30] [i29] [j32] [j30] [j29] [j28] [i25] [i24] [i23] [i22] [c24] [c23] [c22] [c21] [c20] [c17] [i19] [i18] [i17] [j24]
[j56] [j54] [j53] [c44] [j51] [c43] [c41] [c40] [c39] [i38] [i37] [j49] [j48] [j46] [j45] [j44] [c38] [c37] [c36] [c35] [c34] [j43] [j42] [j38] [j36] [j35] [j34] [c32] [c31] [c30] [c29] [c28] [i32] [i30] [i29] [j30] [i25] [i24] [i23] [i22] [c23] [c18] [i17] [j23] [j22] [c15] [i15] [i14] [i10] [c13] [c12] [i9] [i8] [i6] [j20] [c11] [c10] [i5] [i4] [j19] [j18] [i3] [c9] [c8] [c7] [c6] [c5] [c4] [i2] [i1] [j13] [j12] [j11] [j10] [j8] [j7] [j3] [c3] [c1]
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