Yuanyuan Liu

According to our database, Yuanyuan Liu authored at least 70 papers between 2011 and 2024.

Collaborative distances:

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

2024

Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering.

Hongying Liu, Linlin Yang, Longge Zhang, Fanhua Shang, Yuanyuan Liu, Lijun Wang

Sensors, June, 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

A single frame and multi-frame joint network for 360-degree panorama video super-resolution.

Hongying Liu, Wanhao Ma, Zhubo Ruan, Chaowei Fang, Fanhua Shang, Yuanyuan Liu, Lijun Wang, Chaoli Wang, Dongmei Jiang

Eng. Appl. Artif. Intell., 2024

FedBCGD: Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning.

Junkang Liu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Yuangang Li, YunXiang Gong

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 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

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

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

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

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

Multi Recursive Residual Dense Attention GAN for Perceptual Image Super Resolution.

Linlin Yang, Hongying Liu, Yiming Li, Wenhao Zhou, Yuanyuan Liu, Xiaobiao Di, Lei Wang, Chuanwen Li

Proceedings of the Intelligence Science IV, 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

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

Learned Interpretable Residual Extragradient ISTA for Sparse Coding.

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

CoRR, 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

Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications.

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

Sensors, 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

2019

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

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

CoRR, 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 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

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

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

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

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

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

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

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

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

Learning Spectral Embedding for Semi-supervised Clustering.

Fanhua Shang, Yuanyuan Liu, Fei Wang

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