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Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks

Nov 29, 2020
Pengtao Xu, Jian Cao, Fanhua Shang, Wenyu Sun, Pu Li


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Differentially Private ADMM Algorithms for Machine Learning

Oct 31, 2020
Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong

* 11 pages, 2 figures 

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Boosting Gradient for White-Box Adversarial Attacks

Oct 21, 2020
Hongying Liu, Zhenyu Zhou, Fanhua Shang, Xiaoyu Qi, Yuanyuan Liu, Licheng Jiao

* 9 pages,6 figures 

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

Aug 24, 2020
Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang

* 10 pages, 5 figures, submitted to an international peer-review journal 

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Video Super Resolution Based on Deep Learning: A comprehensive survey

Jul 25, 2020
Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang, Yuanyuan Liu


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Data Augmentation Imbalance For Imbalanced Attribute Classification

May 21, 2020
Yang Hu, Xiaying Bai, Pan Zhou, Fanhua Shang, Shengmei Shen

* This paper needs further revision 

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

May 10, 2020
Miaohua Zhang, Yongsheng Gao, Fanhua Shang


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Deep Residual-Dense Lattice Network for Speech Enhancement

Feb 27, 2020
Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao, Jun Zhou, Kuldip K. Paliwal, Fanhua Shang

* 8 pages, Accepted by AAAI-2020 

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

Dec 02, 2019
Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Jiacheng Zhuo

* 7 pages, 3 figures, Appeared at the Data Science Meets Optimization Workshop (DSO) at IJCAI'19 

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signADAM: Learning Confidences for Deep Neural Networks

Jul 21, 2019
Dong Wang, Yicheng Liu, Wenwo Tang, Fanhua Shang, Hongying Liu, Qigong Sun, Licheng Jiao

* 11 pages, 7 figures 

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

Jul 17, 2019
Hongying Liu, Xiongjie Shen, Fanhua Shang, Fei Wang

* 9 pages, 4 figures 

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

May 31, 2019
Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren, Licheng Jiao

* 9 pages, 2 figures, Proc. 33rd AAAI Conf. Artif. Intell., 2019 

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

Oct 28, 2018
Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao

* 46 pages, 25 figures. IEEE Transactions on Knowledge and Data Engineering, accepted in October, 2018. arXiv admin note: substantial text overlap with arXiv:1704.04966 

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

Oct 11, 2018
Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin

* IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(9): 2066-2080, 2018 
* 29 pages, 19 figures 

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ASVRG: Accelerated Proximal SVRG

Oct 07, 2018
Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin

* 32 pages, 3 figures 

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A Unified Approximation Framework for Deep Neural Networks

Jul 27, 2018
Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

* 10 pages, 4 figures, 2 tables 

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A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates

Jun 28, 2018
Kaiwen Zhou, Fanhua Shang, James Cheng

* ICML2018 

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Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization

Feb 28, 2018
Fanhua Shang, Yuanyuan Liu, James Cheng

* 26 pages, 7 figures, AISTATS 2016. arXiv admin note: text overlap with arXiv:1606.01245 

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Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization

Feb 26, 2018
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin K. W. Ng, Yuichi Yoshida

* 24 pages, 10 figures, AISTATS 2018. arXiv admin note: text overlap with arXiv:1703.06807 

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Accelerated Variance Reduced Stochastic ADMM

Jul 11, 2017
Yuanyuan Liu, Fanhua Shang, James Cheng

* 16 pages, 5 figures, Appears in Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI), San Francisco, California, USA, pp. 2287--2293, 2017 

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Guaranteed Sufficient Decrease for Variance Reduced Stochastic Gradient Descent

Jun 04, 2017
Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida

* 25 pages, 8 figures 

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

Apr 17, 2017
Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo

* Corrected a few typos in this version 

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

Apr 17, 2017
Fanhua Shang

* 36 pages, 10 figures. The simple variant of SVRG is much better than the best-known stochastic method, Katyusha 

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Unified Scalable Equivalent Formulations for Schatten Quasi-Norms

Nov 27, 2016
Fanhua Shang, Yuanyuan Liu, James Cheng

* 21 pages. CUHK Technical Report CSE-ShangLC20160307, March 7, 2016 

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Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization

Jun 04, 2016
Fanhua Shang, Yuanyuan Liu, James Cheng

* 16 pages, 5 figures, Appears in Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, pp. 2016--2022, 2016 

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Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning

Jan 16, 2016
Fanhua Shang, James Cheng, Hong Cheng

* 18 pages, 10 figures 

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

Sep 03, 2014
Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng

* 28 pages, 9 figures 

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Generalized Higher-Order Tensor Decomposition via Parallel ADMM

Jul 05, 2014
Fanhua Shang, Yuanyuan Liu, James Cheng

* 9 pages, 5 figures, AAAI 2014 

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