Jinshan Zeng

According to our database, Jinshan Zeng authored at least 78 papers between 2011 and 2025.

Collaborative distances:

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

2025

EdgeFont: Enhancing style and content representations in few-shot font generation with multi-scale edge self-supervision.

Yefei Wang, Kangyue Xiong, Yiyang Yuan, Jinshan Zeng

Expert Syst. Appl., 2025

2024

Sequential Manipulation Against Rank Aggregation: Theory and Algorithm.

Ke Ma, Qianqian Xu, Jinshan Zeng, Wei Liu, Xiaochun Cao, Yingfei Sun, Qingming Huang

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Combining Low-Rank and Deep Plug-and-Play Priors for Snapshot Compressive Imaging.

Yong Chen, Xinfeng Gui, Jinshan Zeng, Xi-Le Zhao, Wei He

IEEE Trans. Neural Networks Learn. Syst., November, 2024

A guidable nonlocal low-rank approximation model for hyperspectral image denoising.

Yong Chen, Juan Zhang, Jinshan Zeng, Wenzhen Lai, Xinfeng Gui, Tai-Xiang Jiang

Signal Process., February, 2024

Hyperspectral Compressive Snapshot Reconstruction via Coupled Low-Rank Subspace Representation and Self-Supervised Deep Network.

Yong Chen, Wenzhen Lai, Wei He, Xi-Le Zhao, Jinshan Zeng

IEEE Trans. Image Process., 2024

Fast Large-Scale Hyperspectral Image Denoising via Noniterative Low-Rank Subspace Representation.

Yong Chen, Jinshan Zeng, Wei He, Xi-Le Zhao, Tai-Xiang Jiang, Qing Huang

IEEE Trans. Geosci. Remote. Sens., 2024

Thick Cloud Removal in Multitemporal Remote Sensing Images via Low-Rank Regularized Self-Supervised Network.

Yong Chen, Maolin Chen, Wei He, Jinshan Zeng, Min Huang, Yu-Bang Zheng

IEEE Trans. Geosci. Remote. Sens., 2024

Unidirectional Spatial and Spectral Smoothed Tensor Ring Decomposition for Hyperspectral Image Denoising and Destriping.

Yang Zhou, Yong Chen, Jinshan Zeng, Wei He, Min Huang

IEEE Geosci. Remote. Sens. Lett., 2024

On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness.

Shengkun Zhu, Jinshan Zeng, Sheng Wang, Yuan Sun, Xiaodong Li, Yuan Yao, Zhiyong Peng

CoRR, 2024

Efficient k-means with Individual Fairness via Exponential Tilting.

Shengkun Zhu, Jinshan Zeng, Yuan Sun, Sheng Wang, Xiaodong Li, Zhiyong Peng

CoRR, 2024

SCA-Font: Enhancing Few-Shot Generation with Style-Content Aggregation.

Yefei Wang, Sunzhe Yang, Kangyue Xiong, Jinshan Zeng

Proceedings of the International Joint Conference on Neural Networks, 2024

CLIP-Font: Sementic Self-Supervised Few-Shot Font Generation with Clip.

Jialu Xiong, Yefei Wang, Jinshan Zeng

Proceedings of the IEEE International Conference on Acoustics, 2024

CLIP-MSA: Incorporating Inter-Modal Dynamics and Common Knowledge to Multimodal Sentiment Analysis With Clip.

Qi Huang, Pingting Cai, Tanyue Nie, Jinshan Zeng

Proceedings of the IEEE International Conference on Acoustics, 2024

SCI-Font: Enhancing Content-Style Representation for Chinese Calligraphy Generation with Skeleton, Contour and Inexact Paired Data.

Yan Zhang, Yefei Wang, Jialu Xiong, Jie Zhou, Jinshan Zeng

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

InterpretARA: Enhancing Hybrid Automatic Readability Assessment with Linguistic Feature Interpreter and Contrastive Learning.

Jinshan Zeng, Xianchao Tong, Xianglong Yu, Wenyan Xiao, Qing Huang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

F3KM: Federated, Fair, and Fast k-means.

Shengkun Zhu, Quanqing Xu, Jinshan Zeng, Sheng Wang, Yuan Sun, Zhifeng Yang, Chuanhui Yang, Zhiyong Peng

Proc. ACM Manag. Data, December, 2023

A Tale of HodgeRank and Spectral Method: Target Attack Against Rank Aggregation is the Fixed Point of Adversarial Game.

Ke Ma, Qianqian Xu, Jinshan Zeng, Guorong Li, Xiaochun Cao, Qingming Huang

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Exploring Structural Sparsity of Deep Networks Via Inverse Scale Spaces.

Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, Yuan Yao

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Zero-Shot Chinese Character Recognition with Stroke- and Radical-Level Decompositions.

Jinshan Zeng, Ruiying Xu, Yu Wu, Hongwei Li, Jiaxing Lu

Proceedings of the International Joint Conference on Neural Networks, 2023

Enhancing Chinese Calligraphy Generation with Contour and Region-aware Attention.

Jinshan Zeng, Ling Tu, Jie Zhou, Yefei Wang, Jiguo Zeng

Proceedings of the International Joint Conference on Neural Networks, 2023

PromptARA: Improving Deep Representation in Hybrid Automatic Readability Assessment with Prompt and Orthogonal Projection.

Jinshan Zeng, Xianglong Yu, Xianchao Tong, Wenyan Xiao

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Hyperspectral and Multispectral Image Fusion Using Factor Smoothed Tensor Ring Decomposition.

Yong Chen, Jinshan Zeng, Wei He, Xi-Le Zhao, Ting-Zhu Huang

IEEE Trans. Geosci. Remote. Sens., 2022

Exploring Nonlocal Group Sparsity Under Transform Learning for Hyperspectral Image Denoising.

Yong Chen, Wei He, Xi-Le Zhao, Ting-Zhu Huang, Jinshan Zeng, Hui Lin

IEEE Trans. Geosci. Remote. Sens., 2022

Hyperspectral Image Denoising Using Factor Group Sparsity-Regularized Nonconvex Low-Rank Approximation.

Yong Chen, Ting-Zhu Huang, Wei He, Xi-Le Zhao, Hongyan Zhang, Jinshan Zeng

IEEE Trans. Geosci. Remote. Sens., 2022

Poisoning Attack Against Estimating From Pairwise Comparisons.

Ke Ma, Qianqian Xu, Jinshan Zeng, Xiaochun Cao, Qingming Huang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Fully corrective gradient boosting with squared hinge: Fast learning rates and early stopping.

Jinshan Zeng, Min Zhang, Shao-Bo Lin

Neural Networks, 2022

Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints.

Jinshan Zeng, Wotao Yin, Ding-Xuan Zhou

J. Sci. Comput., 2022

SGCE-Font: Skeleton Guided Channel Expansion for Chinese Font Generation.

Jie Zhou, Yefei Wang, Yiyang Yuan, Qing Huang, Jinshan Zeng

CoRR, 2022

StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding.

Jinshan Zeng, Yefei Wang, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan Yao

CoRR, 2022

STAR: Zero-Shot Chinese Character Recognition with Stroke- and Radical-Level Decompositions.

Jinshan Zeng, Ruiying Xu, Yu Wu, Hongwei Li, Jiaxing Lu

CoRR, 2022

Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd Counting.

Yunxin Liu, Qiaosi Yi, Jinshan Zeng

CoRR, 2022

CodeGen-Test: An Automatic Code Generation Model Integrating Program Test Information.

Maosheng Zhong, Gen Liu, Hongwei Li, Jiangling Kuang, Jinshan Zeng, Mingwen Wang

CoRR, 2022

Image Processing and Control of Tracking Intelligent Vehicle Based on Grayscale Camera.

Jian Zhang, Yufan Liu, Ao Li, Jinshan Zeng, Hongtu Xie

Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022

Enhancing Automatic Readability Assessment with Pre-training and Soft Labels for Ordinal Regression.

Jinshan Zeng, Yudong Xie, Xianglong Yu, John Lee, Ding-Xuan Zhou

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Random Sketching for Neural Networks With ReLU.

Di Wang, Jinshan Zeng, Shao-Bo Lin

IEEE Trans. Neural Networks Learn. Syst., 2021

Fast Stochastic Ordinal Embedding With Variance Reduction and Adaptive Step Size.

Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan Yao

IEEE Trans. Knowl. Data Eng., 2021

On ADMM in Deep Learning: Convergence and Saturation-Avoidance.

Jinshan Zeng, Shao-Bo Lin, Yuan Yao, Ding-Xuan Zhou

J. Mach. Learn. Res., 2021

On Stochastic Variance Reduced Gradient Method for Semidefinite Optimization.

Jinshan Zeng, Yixuan Zha, Ke Ma, Yuan Yao

CoRR, 2021

StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding.

Jinshan Zeng, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan Yao

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths.

Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

On Global Linear Convergence in Stochastic Nonconvex Optimization for Semidefinite Programming.

Jinshan Zeng, Ke Ma, Yuan Yao

IEEE Trans. Signal Process., 2019

Constructive Neural Network Learning.

Shaobo Lin, Jinshan Zeng, Xiaoqin Zhang

IEEE Trans. Cybern., 2019

Fast Learning With Polynomial Kernels.

Shaobo Lin, Jinshan Zeng

IEEE Trans. Cybern., 2019

Global Convergence of ADMM in Nonconvex Nonsmooth Optimization.

Yu Wang, Wotao Yin, Jinshan Zeng

J. Sci. Comput., 2019

Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size.

Ke Ma, Jinshan Zeng, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan Yao

CoRR, 2019

Fast Polynomial Kernel Classification for Massive Data.

Jinshan Zeng, Minrun Wu, Shao-Bo Lin, Ding-Xuan Zhou

CoRR, 2019

Parsimonious Deep Learning: A Differential Inclusion Approach with Global Convergence.

Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao

CoRR, 2019

A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning.

Jinshan Zeng, Shaobo Lin, Yuan Yao

CoRR, 2019

Global Convergence of Block Coordinate Descent in Deep Learning.

Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao

Proceedings of the 36th International Conference on Machine Learning, 2019

Image Smoothing Via Gradient Sparsity and Surface Area Minimization.

Jun Liu, Ming Yan, Jinshan Zeng, Tieyong Zeng

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

2018

On Nonconvex Decentralized Gradient Descent.

Jinshan Zeng, Wotao Yin

IEEE Trans. Signal Process., 2018

Greedy Criterion in Orthogonal Greedy Learning.

Lin Xu, Shaobo Lin, Jinshan Zeng, Xia Liu, Yi Fang, Zongben Xu

IEEE Trans. Cybern., 2018

Corrigendum to "GAITA: A Gauss-Seidel iterative thresholding algorithm for l_q regularized least squares regression" [J. Comput. Appl. Math. 319 (2017) 220-235].

Jinshan Zeng, Zhimin Peng, Shaobo Lin

J. Comput. Appl. Math., 2018

Block Coordinate Descent for Deep Learning: Unified Convergence Guarantees.

Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao

CoRR, 2018

A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training.

Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao

Proceedings of the 6th International Conference on Learning Representations, 2018

Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction.

Jinshan Zeng, Ke Ma, Yuan Yao

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Stochastic Non-Convex Ordinal Embedding With Stabilized Barzilai-Borwein Step Size.

Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan Yao

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

A fast proximal gradient algorithm for decentralized composite optimization over directed networks.

Jinshan Zeng, Tao He, Mingwen Wang

Syst. Control. Lett., 2017

Learning Rates for Classification with Gaussian Kernels.

Shaobo Lin, Jinshan Zeng, Xiangyu Chang

Neural Comput., 2017

GAITA: A Gauss-Seidel iterative thresholding algorithm for ℓ_q regularized least squares regression.

Jinshan Zeng, Zhimin Peng, Shaobo Lin

J. Comput. Appl. Math., 2017

2016

Sparse Regularization: Convergence Of Iterative Jumping Thresholding Algorithm.

Jinshan Zeng, Shaobo Lin, Zongben Xu

IEEE Trans. Signal Process., 2016

A Proximal Gradient Algorithm for Decentralized Composite Optimization over Directed Networks.

Jinshan Zeng, Tao He, Mingwen Wang

CoRR, 2016

Greedy Criterion in Orthogonal Greedy Learning.

Lin Xu, Shaobo Lin, Jinshan Zeng, Xia Liu, Zongben Xu

CoRR, 2016

2015

Linear Convergence of Adaptively Iterative Thresholding Algorithms for Compressed Sensing.

Yu Wang, Jinshan Zeng, Zhimin Peng, Xiangyu Chang, Zongben Xu

IEEE Trans. Signal Process., 2015

Error Estimate for Spherical Neural Networks Interpolation.

Shaobo Lin, Jinshan Zeng, Zongben Xu

Neural Process. Lett., 2015

Jackson-type inequalities for spherical neural networks with doubling weights.

Shaobo Lin, Jinshan Zeng, Lin Xu, Zongben Xu

Neural Networks, 2015

Indoor Fingerprinting Localization and Tracking System Using Particle Swarm Optimization and Kalman Filter.

Genming Ding, Zhenhui Tan, Jinsong Wu, Jinshan Zeng, Lingwen Zhang

IEICE Trans. Commun., 2015

ExtraPush for Convex Smooth Decentralized Optimization over Directed Networks.

Jinshan Zeng, Wotao Yin

CoRR, 2015

A Gauss-Seidel Iterative Thresholding Algorithm for lq Regularized Least Squares Regression.

Jinshan Zeng, Zhimin Peng, Shaobo Lin

CoRR, 2015

2014

L_1/2 Regularization: Convergence of Iterative Half Thresholding Algorithm.

Jinshan Zeng, Shaobo Lin, Yao Wang, Zongben Xu

IEEE Trans. Signal Process., 2014

Sparse solution of underdetermined linear equations via adaptively iterative thresholding.

Jinshan Zeng, Shaobo Lin, Zongben Xu

Signal Process., 2014

Learning Rates of <i>l^q</i> Coefficient Regularization Learning with Gaussian Kernel.

Shaobo Lin, Jinshan Zeng, Jian Fang, Zongben Xu

Neural Comput., 2014

Greedy metrics in orthogonal greedy learning.

Lin Xu, Shaobo Lin, Jinshan Zeng, Zongben Xu

CoRR, 2014

2013

Accelerated <i>L</i>_1/2 regularization based SAR imaging via BCR and reduced Newton skills.

Jinshan Zeng, Zongben Xu, Bingchen Zhang, Wen Hong, Yirong Wu

Signal Process., 2013

Learning rates of l^q coefficient regularization learning with Gaussian kernel.

Shaobo Lin, Jinshan Zeng, Jian Fang, Zongben Xu

CoRR, 2013

2012

Sparse SAR imaging based on L 1/2 regularization.

Jinshan Zeng, Jian Fang, Zongben Xu

Sci. China Inf. Sci., 2012

Efficient DPCA SAR imaging with fast iterative spectrum reconstruction method.

Jian Fang, Jinshan Zeng, Zongben Xu, Yao Zhao

Sci. China Inf. Sci., 2012

2011

SAR imaging from compressed measurements based on L1/2 regularization.

Jinshan Zeng, Zongben Xu, Hai Jiang, Bingchen Zhang, Wen Hong, Yirong Wu

Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011