Yuanyuan Liu

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 64

Top Topics

Tensor Decomposition

Machine Learning

Norm Minimization

Super Resolution

Top Venues

Publications

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)
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 (2024)
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 (2024)
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) (2024)
Linlin Yang, Hongying Liu, Fanhua Shang, Yuanyuan Liu
Adaptive Non-Local Generative Adversarial Networks for Low-Dose CT Image Denoising. ICASSP (2023)
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 (2023)
Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Xiaosen Wang
Boosting Adversarial Transferability by Achieving Flat Local Maxima. CoRR (2023)
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)
Zhijin Ge, Xiaosen Wang, Hongying Liu, Fanhua Shang, Yuanyuan Liu
Boosting Adversarial Transferability by Achieving Flat Local Maxima. NeurIPS (2023)
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) (2023)
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)
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)
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)
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) (2022)
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)
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) (2022)
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) (2022)
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) (2022)
Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu
HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks. AAAI (2022)
Linlin Yang, Hongying Liu, Yiming Li, Wenhao Zhou, Yuanyuan Liu, Xiaobiao Di, Lei Wang, Chuanwen Li
Multi Recursive Residual Dense Attention GAN for Perceptual Image Super Resolution. IFIP TC12 ICIS (2022)
Dong Wang, Yicheng Liu, Liangji Fang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
Balanced Gradient Penalty Improves Deep Long-Tailed Learning. ACM Multimedia (2022)
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 (2022)
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) (2021)
Fanhua Shang, Zhihui Zhang, Tao Xu, Yuanyuan Liu, Hongying Liu
Principal component analysis in the stochastic differential privacy model. UAI (2021)
Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. IJCAI (2021)
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) (2021)
Chaolong Zhang, Yuanyuan Liu, Fanhua Shang, Yangyang Li, Hongying Liu
A Novel Learned Primal-Dual Network for Image Compressive Sensing. IEEE Access 9 (2021)
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 (2021)
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)
Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling. CoRR (2021)
Hongying Liu, Ruyi Luo, Fanhua Shang, Mantang Niu, Yuanyuan Liu
Progressive Semantic Matching for Video-Text Retrieval. ACM Multimedia (2021)
Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. CoRR (2021)
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 (2021)
Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu
Learned Interpretable Residual Extragradient ISTA for Sparse Coding. CoRR (2021)
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 (2021)
Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding. AAAI (2021)
Hongying Liu, Zhenyu Zhou, Fanhua Shang, Xiaoyu Qi, Yuanyuan Liu, Licheng Jiao
Boosting Gradient for White-Box Adversarial Attacks. CoRR (2020)
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) (2020)
Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang, Yuanyuan Liu
Video Super Resolution Based on Deep Learning: A comprehensive survey. CoRR (2020)
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 (2020)
Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong
Differentially Private ADMM Algorithms for Machine Learning. CoRR (2020)
Yuanyuan Liu, Fanhua Shang, Licheng Jiao
Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor. IJCAI (2019)
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)
Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Jiacheng Zhuo
Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization. CoRR (2019)
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)
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR (2018)
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) (2018)
Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin
Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. CoRR (2018)
Fanhua Shang, Yuanyuan Liu, James Cheng
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. CoRR (2018)
Fanhua Shang, Yuanyuan Liu, James Cheng, Da Yan
Fuzzy Double Trace Norm Minimization for Recommendation Systems. IEEE Trans. Fuzzy Syst. 26 (4) (2018)
Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. NIPS (2017)
Yuanyuan Liu, Tan Lee, P. C. Ching, Thomas K. T. Law, Kathy Y. S. Lee
Acoustic Assessment of Disordered Voice with Continuous Speech Based on Utterance-Level ASR Posterior Features. INTERSPEECH (2017)
Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. CoRR (2017)
Yuanyuan Liu, Fanhua Shang, James Cheng
Accelerated Variance Reduced Stochastic ADMM. CoRR (2017)
Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo
Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. CoRR (2017)
Yuanyuan Liu, Fanhua Shang, James Cheng
Accelerated Variance Reduced Stochastic ADMM. AAAI (2017)
Fanhua Shang, Yuanyuan Liu, James Cheng
Unified Scalable Equivalent Formulations for Schatten Quasi-Norms. CoRR (2016)
Fanhua Shang, Yuanyuan Liu, James Cheng
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. AISTATS (2016)
Fanhua Shang, Yuanyuan Liu, James Cheng
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. CoRR (2016)
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) (2016)
Fanhua Shang, Yuanyuan Liu, James Cheng
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. AAAI (2016)
Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, Hong Cheng
Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data. IEEE Trans. Cybern. 45 (11) (2015)
Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning. CoRR (2015)
Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng
Robust bilinear factorization with missing and grossly corrupted observations. Inf. Sci. 307 (2015)
Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng
Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. UAI (2014)
Fanhua Shang, Yuanyuan Liu, James Cheng
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. CoRR (2014)
Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, Hanghang Tong
Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. SDM (2014)
Fanhua Shang, Yuanyuan Liu, James Cheng
Generalized Higher-Order Tensor Decomposition via Parallel ADMM. AAAI (2014)
Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng
Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. NIPS (2014)
Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization. ICDM (2014)
Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
Robust Principal Component Analysis with Missing Data. CIKM (2014)
Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng
Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations. CoRR (2014)
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 (2013)
Yuanyuan Liu, Fanhua Shang
An Efficient Matrix Factorization Method for Tensor Completion. IEEE Signal Process. Lett. 20 (4) (2013)
Yuanyuan Liu, Licheng Jiao, Fanhua Shang
An efficient matrix factorization based low-rank representation for subspace clustering. Pattern Recognit. 46 (1) (2013)
Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Hanghang Tong
Semi-supervised learning with nuclear norm regularization. Pattern Recognit. 46 (8) (2013)
Yuanyuan Liu, Licheng Jiao, Fanhua Shang
A fast tri-factorization method for low-rank matrix recovery and completion. Pattern Recognit. 46 (1) (2013)
Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Fei Wang
Learning spectral embedding via iterative eigenvalue thresholding. CIKM (2012)
Licheng Jiao, Fanhua Shang, Fei Wang, Yuanyuan Liu
Fast semi-supervised clustering with enhanced spectral embedding. Pattern Recognit. 45 (12) (2012)
Fanhua Shang, Licheng Jiao, Yuanyuan Liu
Integrating Spectral Kernel Learning and Constraints in Semi-Supervised Classification. Neural Process. Lett. 36 (2) (2012)
Fanhua Shang, Yuanyuan Liu, Fei Wang
Learning Spectral Embedding for Semi-supervised Clustering. ICDM (2011)