Yuanyuan Liu - RankMe

96 papers A* 24A 7B 1C 1Misc 1Journal 59Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models. AAAI Junkang Liu, Fanhua Shang, Hongying Liu, Yuxuan Tian, Yuanyuan Liu, Jin Liu, Kewen Zhu, Zhouchen Lin
2026	J	`jnl`	FedBCD:Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning. CoRR Junkang Liu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Yuangang Li, YunXiang Gong
2026	J	`jnl`	FedNSAM:Consistency of Local and Global Flatness for Federated Learning. CoRR Junkang Liu, Fanhua Shang, Yuxuan Tian, Hongying Liu, Yuanyuan Liu
2026	J	`jnl`	Taming Preconditioner Drift: Unlocking the Potential of Second-Order Optimizers for Federated Learning on Non-IID Data. CoRR Junkang Liu, Fanhua Shang, Hongying Liu, Jin Liu, Weixin An, Yuanyuan Liu
2025	A*	`conf`	Consistency of Local and Global Flatness for Federated Learning. ACM Multimedia Junkang Liu, Fanhua Shang, Yuxuan Tian, Hongying Liu, Yuanyuan Liu
2025	J	`jnl`	DEs-Inspired Accelerated Unfolded Linearized ADMM Networks for Inverse Problems. IEEE Trans. Neural Networks Learn. Syst. Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu, Licheng Jiao
2025	J	`jnl`	DP-FedPGN: Finding Global Flat Minima for Differentially Private Federated Learning via Penalizing Gradient Norm. CoRR Junkang Liu, Yuxuan Tian, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Junchao Zhou, Ding Daorui
2025	J	`jnl`	Distillation guided deep unfolding network with frequency hierarchical regularization for low-dose CT image denoising. Neurocomputing Linlin Yang, Hongying Liu, Yuanyuan Liu, Fanhua Shang, Liang Wan, Licheng Jiao
2025	J	`jnl`	FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models. CoRR Junkang Liu, Fanhua Shang, Kewen Zhu, Hongying Liu, Yuanyuan Liu, Jin Liu
2025	J	`jnl`	FedMuon: Accelerating Federated Learning with Matrix Orthogonalization. CoRR Junkang Liu, Fanhua Shang, Junchao Zhou, Hongying Liu, Yuanyuan Liu, Jin Liu
2025	J	`jnl`	FedSWA: Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging. CoRR Junkang Liu, Yuanyuan Liu, Fanhua Shang, Hongying Liu, Jin Liu, Wei Feng
2025	A*	`conf`	Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging. ICML Junkang Liu, Yuanyuan Liu, Fanhua Shang, Hongying Liu, Jin Liu, Wei Feng
2025	A*	`conf`	Unsupervised Degradation Representation Aware Transform for Real-World Blind Image Super-Resolution. AAAI Sen Chen, Hongying Liu, Chaowei Fang, Fanhua Shang, Yuanyuan Liu, Liang Wan, Dongmei Jiang, Yaowei Wang
2024	J	`jnl`	A single frame and multi-frame joint network for 360-degree panorama video super-resolution. Eng. Appl. Artif. Intell. Hongying Liu, Wanhao Ma, Zhubo Ruan, Chaowei Fang, Fanhua Shang, Yuanyuan Liu, Lijun Wang, Chaoli Wang, Dongmei Jiang
2024	J	`jnl`	Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering. Sensors Hongying Liu, Linlin Yang, Longge Zhang, Fanhua Shang, Yuanyuan Liu, Lijun Wang
2024	J	`jnl`	Arbitrary-scale Super-resolution via Deep Learning: A Comprehensive Survey. Inf. Fusion Hongying Liu, Zekun Li, Fanhua Shang, Yuanyuan Liu, Liang Wang, Wei Feng, Radu Timofte
2024	A*	`conf`	FedBCGD: Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning. ACM Multimedia Junkang Liu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Yuangang Li, YunXiang Gong
2024	J	`jnl`	Gradient Correction for White-Box Adversarial Attacks. IEEE Trans. Neural Networks Learn. Syst. Hongying Liu, Zhijin Ge, Zhenyu Zhou, Fanhua Shang, Yuanyuan Liu, Licheng Jiao
2024	A*	`conf`	Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications. NeurIPS Weixin An, Yuanyuan Liu, Fanhua Shang, Hongying Liu
2024	A*	`conf`	SAVSR: Arbitrary-Scale Video Super-Resolution via a Learned Scale-Adaptive Network. AAAI Zekun Li, Hongying Liu, Fanhua Shang, Yuanyuan Liu, Liang Wan, Wei Feng
2023	A*	`conf`	A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization. NeurIPS Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu, Zhouchen Lin
2023	Misc	`conf`	Adaptive Non-Local Generative Adversarial Networks for Low-Dose CT Image Denoising. ICASSP Linlin Yang, Hongying Liu, Fanhua Shang, Yuanyuan Liu
2023	A*	`conf`	Boosting Adversarial Transferability by Achieving Flat Local Maxima. NeurIPS Zhijin Ge, Xiaosen Wang, Hongying Liu, Fanhua Shang, Yuanyuan Liu
2023	J	`jnl`	Boosting Adversarial Transferability by Achieving Flat Local Maxima. CoRR Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Xiaosen Wang
2023	A*	`conf`	Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer. ACM Multimedia Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Liang Wan, Wei Feng, Xiaosen Wang
2023	J	`jnl`	Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer. CoRR Zhijin Ge, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Liang Wan, Wei Feng, Xiaosen Wang
2023	J	`jnl`	Lightweight Super-Resolution with Self-Calibrated Convolution for Panoramic Videos. Sensors Fanjie Shang, Hongying Liu, Wanhao Ma, Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Lijun Wang, Zhenyu Zhou
2022	A*	`conf`	A Numerical DEs Perspective on Unfolded Linearized ADMM Networks for Inverse Problems. ACM Multimedia Weixin An, Yingjie Yue, Yuanyuan Liu, Fanhua Shang, Hongying Liu
2022	J	`jnl`	Asynchronous Parallel, Sparse Approximated SVRG for High-Dimensional Machine Learning. IEEE Trans. Knowl. Data Eng. Fanhua Shang, Hua Huang, Jun Fan, Yuanyuan Liu, Hongying Liu, JianHui Liu
2022	A*	`conf`	Balanced Gradient Penalty Improves Deep Long-Tailed Learning. ACM Multimedia Dong Wang, Yicheng Liu, Liangji Fang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2022	J	`jnl`	Efficient Gradient Support Pursuit With Less Hard Thresholding for Cardinality-Constrained Learning. IEEE Trans. Neural Networks Learn. Syst. Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Pan Zhou, Maoguo Gong
2022	A*	`conf`	HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks. AAAI Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2022	A*	`conf`	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 Yuanyuan Liu, Fanhua Shang, Weixin An, Hongying Liu, Zhouchen Lin
2022	J	`jnl`	Laplacian Smoothing Stochastic ADMMs With Differential Privacy Guarantees. IEEE Trans. Inf. Forensics Secur. Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu, Wei Feng
2022	J	`jnl`	Loopless Variance Reduced Stochastic ADMM for Equality Constrained Problems in IoT Applications. IEEE Internet Things J. Yuanyuan Liu, Jiacheng Geng, Fanhua Shang, Weixin An, Hongying Liu, Qi Zhu
2022	C	`conf`	Multi Recursive Residual Dense Attention GAN for Perceptual Image Super Resolution. ICIS Linlin Yang, Hongying Liu, Yiming Li, Wenhao Zhou, Yuanyuan Liu, Xiaobiao Di, Lei Wang, Chuanwen Li
2022	B	`conf`	PWPROP: A Progressive Weighted Adaptive Method for Training Deep Neural Networks. ICTAI Dong Wang, Tao Xu, Huatian Zhang, Fanhua Shang, Hongying Liu, Yuanyuan Liu, Shengmei Shen
2022	J	`jnl`	Video super-resolution based on deep learning: a comprehensive survey. Artif. Intell. Rev. Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte
2021	J	`jnl`	A Novel Learned Primal-Dual Network for Image Compressive Sensing. IEEE Access Chaolong Zhang, Yuanyuan Liu, Fanhua Shang, Yangyang Li, Hongying Liu
2021	J	`jnl`	Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. Yuanyuan Liu, Fanhua Shang, Hongying Liu, Lin Kong, Licheng Jiao, Zhouchen Lin
2021	A*	`conf`	Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. IJCAI Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2021	J	`jnl`	Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning. CoRR Hua Huang, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2021	J	`jnl`	Deep Fuzzy Graph Convolutional Networks for PolSAR Imagery Pixelwise Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Hongying Liu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Derui Lv, Shuyuan Yang
2021	J	`jnl`	Differentially Private ADMM Algorithms for Machine Learning. IEEE Trans. Inf. Forensics Secur. Fanhua Shang, Tao Xu, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong
2021	J	`jnl`	Efficient Asynchronous Semi-Stochastic Block Coordinate Descent Methods for Large-Scale SVD. IEEE Access Fanhua Shang, Zhihui Zhang, Yuanyuan Liu, Hongying Liu, Jing Xu
2021	J	`jnl`	Graph Convolutional Networks by Architecture Search for PolSAR Image Classification. Remote. Sens. Hongying Liu, Derong Xu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Jianhua Lu, Ri Yang
2021	A*	`conf`	Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling. AAAI Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu
2021	J	`jnl`	Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling. CoRR Hongying Liu, Peng Zhao, Zhubo Ruan, Fanhua Shang, Yuanyuan Liu
2021	A*	`conf`	Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding. AAAI Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Zhouchen Lin
2021	J	`jnl`	Learned Interpretable Residual Extragradient ISTA for Sparse Coding. CoRR Lin Kong, Wei Sun, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2021	A	`conf`	Principal component analysis in the stochastic differential privacy model. UAI Fanhua Shang, Zhihui Zhang, Tao Xu, Yuanyuan Liu, Hongying Liu
2021	A*	`conf`	Progressive Semantic Matching for Video-Text Retrieval. ACM Multimedia Hongying Liu, Ruyi Luo, Fanhua Shang, Mantang Niu, Yuanyuan Liu
2020	J	`jnl`	A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution. CoRR Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang
2020	J	`jnl`	Boosting Gradient for White-Box Adversarial Attacks. CoRR Hongying Liu, Zhenyu Zhou, Fanhua Shang, Xiaoyu Qi, Yuanyuan Liu, Licheng Jiao
2020	J	`jnl`	Differentially Private ADMM Algorithms for Machine Learning. CoRR Tao Xu, Fanhua Shang, Yuanyuan Liu, Hongying Liu, Longjie Shen, Maoguo Gong
2020	J	`jnl`	Stochastic Recursive Gradient Support Pursuit and Its Sparse Representation Applications. Sensors Fanhua Shang, Bingkun Wei, Yuanyuan Liu, Hongying Liu, Shuang Wang, Licheng Jiao
2020	J	`jnl`	Video Super Resolution Based on Deep Learning: A comprehensive survey. CoRR Hongying Liu, Zhubo Ruan, Peng Zhao, Fanhua Shang, Linlin Yang, Yuanyuan Liu
2019	—	`conf`	A Stochastic Variance Reduced Extragradient Method for Sparse Machine Learning Problems. ICDM Workshops Lin Kong, Xiaying Bai, Yang Hu, Fanhua Shang, Yuanyuan Liu, Hongying Liu
2019	A*	`conf`	Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor. IJCAI Yuanyuan Liu, Fanhua Shang, Licheng Jiao
2019	J	`jnl`	Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization. CoRR Fanhua Shang, Bingkun Wei, Hongying Liu, Yuanyuan Liu, Jiacheng Zhuo
2018	J	`jnl`	Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. CoRR Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin
2018	J	`jnl`	Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. IEEE Trans. Pattern Anal. Mach. Intell. Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin
2018	J	`jnl`	Fuzzy Double Trace Norm Minimization for Recommendation Systems. IEEE Trans. Fuzzy Syst. Fanhua Shang, Yuanyuan Liu, James Cheng, Da Yan
2018	A	`conf`	Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
2018	J	`jnl`	Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
2018	J	`jnl`	Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng
2017	—	`conf`	Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. NIPS Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, Licheng Jiao
2017	A*	`conf`	Accelerated Variance Reduced Stochastic ADMM. AAAI Yuanyuan Liu, Fanhua Shang, James Cheng
2017	J	`jnl`	Accelerated Variance Reduced Stochastic ADMM. CoRR Yuanyuan Liu, Fanhua Shang, James Cheng
2017	J	`jnl`	Fast Stochastic Variance Reduced Gradient Method with Momentum Acceleration for Machine Learning. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng, Jiacheng Zhuo
2017	J	`jnl`	Variance Reduced Stochastic Gradient Descent with Sufficient Decrease. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
2016	J	`jnl`	Generalized Higher Order Orthogonal Iteration for Tensor Learning and Decomposition. IEEE Trans. Neural Networks Learn. Syst. Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng
2016	A*	`conf`	Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. AAAI Fanhua Shang, Yuanyuan Liu, James Cheng
2016	J	`jnl`	Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng
2016	A	`conf`	Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. AISTATS Fanhua Shang, Yuanyuan Liu, James Cheng
2016	J	`jnl`	Unified Scalable Equivalent Formulations for Schatten Quasi-Norms. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng
2015	J	`jnl`	Regularized Orthogonal Tensor Decompositions for Multi-Relational Learning. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
2015	J	`jnl`	Robust bilinear factorization with missing and grossly corrupted observations. Inf. Sci. Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng
2015	J	`jnl`	Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data. IEEE Trans. Cybern. Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, Hong Cheng
2014	A	`conf`	Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. SDM Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng, Hanghang Tong
2014	—	`conf`	Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. NIPS Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, Hong Cheng
2014	A*	`conf`	Generalized Higher-Order Tensor Decomposition via Parallel ADMM. AAAI Fanhua Shang, Yuanyuan Liu, James Cheng
2014	J	`jnl`	Generalized Higher-Order Tensor Decomposition via Parallel ADMM. CoRR Fanhua Shang, Yuanyuan Liu, James Cheng
2014	A	`conf`	Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. UAI Yuanyuan Liu, Fanhua Shang, Hong Cheng, James Cheng
2014	A*	`conf`	Recovering Low-Rank and Sparse Matrices via Robust Bilateral Factorization. ICDM Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
2014	A	`conf`	Robust Principal Component Analysis with Missing Data. CIKM Fanhua Shang, Yuanyuan Liu, James Cheng, Hong Cheng
2014	J	`jnl`	Structured Low-Rank Matrix Factorization with Missing and Grossly Corrupted Observations. CoRR Fanhua Shang, Yuanyuan Liu, Hanghang Tong, James Cheng, Hong Cheng
2013	J	`jnl`	A fast tri-factorization method for low-rank matrix recovery and completion. Pattern Recognit. Yuanyuan Liu, Licheng Jiao, Fanhua Shang
2013	J	`jnl`	An Efficient Matrix Factorization Method for Tensor Completion. IEEE Signal Process. Lett. Yuanyuan Liu, Fanhua Shang
2013	J	`jnl`	An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion. Neural Networks Yuanyuan Liu, Licheng Jiao, Fanhua Shang, Fei Yin, Fang Liu
2013	J	`jnl`	An efficient matrix factorization based low-rank representation for subspace clustering. Pattern Recognit. Yuanyuan Liu, Licheng Jiao, Fanhua Shang
2013	J	`jnl`	Semi-supervised learning with nuclear norm regularization. Pattern Recognit. Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Hanghang Tong
2012	J	`jnl`	Fast semi-supervised clustering with enhanced spectral embedding. Pattern Recognit. Licheng Jiao, Fanhua Shang, Fei Wang, Yuanyuan Liu
2012	J	`jnl`	Integrating Spectral Kernel Learning and Constraints in Semi-Supervised Classification. Neural Process. Lett. Fanhua Shang, Licheng Jiao, Yuanyuan Liu
2012	A	`conf`	Learning spectral embedding via iterative eigenvalue thresholding. CIKM Fanhua Shang, Licheng Jiao, Yuanyuan Liu, Fei Wang
2011	A*	`conf`	Learning Spectral Embedding for Semi-supervised Clustering. ICDM Fanhua Shang, Yuanyuan Liu, Fei Wang