• Chao Yin, Haiwen Xu, Junfeng Yang, A modified primal-dual algorithm for structured convex optimization with a Lipschitzian term. Journal of the Operations Research Society of China, Accepted.

  • Hongmei Chen, Xingyu Lu, Zengyun Shan, Junfeng Yang, A distributed Bregman PDHG for large-scale resource allocation problems. Journal of Nonlinear and Variational Analysis,  8(6), pages 883-907, 2024.

  • Yaning Jiang, Xingju Cai, Deren Han, Junfeng Yang, Customized Douglas-Rachford splitting methods for structured inverse variational inequality problems, Optimization Methods and Software, 39(2), pages 257-281, 2024.

  • Guoyong Gu, Junfeng Yang, Tight ergodic sublinear convergence rate of the relaxed proximal point algorithm for variational inequalities, Journal of Optimization Theory and Applications, Vol. 202, pages 373-387, 2024.

  • Chao Yin, Junfeng Yang, Golden ratio proximal gradient ADMM for distributed composite convex optimization, Journal of Optimization Theory and Applications,  Vol. 200, pages 895-922, 2024.

  • Xihong Yan, Chuanlong Wang, Junfeng Yang, A note on progressive hedging algorithm for multistage stochastic variational inequalities. Applied Mathematics Letters, 152, 109008, 2024.

  • Danqing Zhou, Haiwen Xu, Junfeng Yang, Proximal alternating direction method of multipliers with convex combination proximal centers, Asia-Pacific Journal of Operational  Research, 2350029, 28 pages, 2023.

  • Hongmei Chen, Guoyong Gu, Junfeng Yang, A golden ratio proximal alternating direction method of multipliers for separable convex optimization. Journal of Global Optimization, 87(2-4):581-602, 2023.

  • Xiaokai Chang, Junfeng Yang, New convergence results of the golden ratio primal dual algorithm, Pacific Journal of Optimization, 19(1):21-43, 2023.

  • Hongmei Chen, Haiwen Xu, Junfeng Yang, A hybrid alternating minimization algorithm for structured convex optimization problems with application in Poissonian image processing. Journal of Industrial and Management Optimization, 19(7):5078-5098, 2023.

  • Guoyong Gu, Junfeng Yang, A unified and tight linear convergence analysis of the relaxed proximal point algorithm, Journal of Industrial and Management Optimization, 19(5):3742-3749, 2023.

  • Xiaokai Chang, Junfeng Yang, GRPDA revisited: relaxed conditions and connection to Chambolle-Pock's primal-dual algorithm. Journal of Scientific Computing, 93:70, 2022.

  • Xiaokai Chang, Junfeng Yang, Hongchao Zhang, Golden ratio primal-dual algorithm with linesearch, SIAM Journal on Optimization, Vol. 32, No. 3, pp. 1584-1613, 2022.

  • Danqing Zhou, Xiaokai Chang, Junfeng Yang, A new primal-dual algorithm for structured convex optimization involving a Lipschitzian term, Pacific Journal of Optimization, Vol. 18, No. 2, pp. 497-517, 2022.

  • Minli Zeng, Junfeng Yang, Guofeng Zhang, On $\tau$ matrix-based approximate inverse preconditioning technique for diagonal-plus-Toeplitz linear systems from spatial fractional diffusion equations, Journal of Computational and Applied Mathematics, Vol. 407, Paper No. 114088, 21, 2022.

  • Xiaokai Chang, Junfeng Yang, A golden ratio primal-dual algorithm for structured convex optimization, Journal of Scientific Computing, 87, 47 (2021).

  • Junfeng Yang, Yin Zhang, Local linear convergence of an ADMM-type splitting framework for equality constrained optimization, Journal of the Operations Research Society of China, Vol. 9, No. 2, pp. 307-319, 2021.

  • Zhenguo Mu, Junfeng Yang, Convergence analysis of a stochastic progressive hedging algorithm for stochastic programming, Statistics, Optimization and Information Computing, Vol. 8, No. 3, pp. 656-667, 2020.

  • Guoyong Gu, Junfeng Yang, Tight sublinear convergence rate of the proximal point algorithm for maximal monotone inclusion problems, SIAM Journal on Optimization, Vol. 30, No. 3, pp. 1905-1921, 2020.

  • Guoyong Gu, Suhong Jiang, and Junfeng Yang, A TVSCAD approach for image deblurring with impulsive noise, Inverse Problems, 33 (2017) 125008.

  • Shiqian Ma and Junfeng Yang, Applications of gauge duality in robust principal component analysis and semidefinite programming, Science China Mathematics, 59(8), p. 1579-1592, 2016.

  • Liusheng Hou, Hongjin He, and Junfeng Yang, A partially parallel splitting method for multiple-block separable convex programming with applications to robust PCA, Computational Optimization and Applications, Vol. 63, pp. 273 - 303, 2016.

  • Caihua Chen, Raymond H. Chan, Shiqian Ma, Junfeng Yang, Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization, SIAM Journal on Imaging Sciences, 8(4):2239--2267, 2015.

  • Caihua Chen, Shiqian Ma, and Junfeng Yang, A general inertial proximal point algorithm for mixed variational inequality problem, SIAM Journal on Optimization, Vol. 25, No. 4 pp. 2120-2142, 2015.

  • Zhida Shen, Zhe Geng, and Junfeng Yang, Image reconstruction from incomplete convolution data via total variation regularization. Statistics, Optimization and Information Computing, 3(1), p. 1-14, 2015.

  • Guoyong Gu, Bingsheng He, and Junfeng Yang, Inexact Alternating-Direction-Based Contraction Methods for Separable Linearly Constrained Convex Optimization, Journal of Optimization Theory and Applications, 163, pp. 105-129, 2014.

  • Junfeng Yang, Defeng Sun, and Kim-Chuan Toh, A proximal point algorithm for log-determinant optimization with group Lasso regularization, SIAM Journal on Optimization, 23 (2013), no. 2, 857–893.

  • Xiaoming Yuan, and Junfeng Yang, Sparse and low rank matrix decomposition via alternating direction method, Pacific Journal of Optimization, 9(1), 167–180, 2013.

  • Junfeng Yang, and Xiaoming Yuan, Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization, Mathematics of Computation, 82(281), 301–329, 2013.

  • Yunhai Xiao, Junfeng Yang, and Xiaoming Yuan, Alternating algorithms for total variation image reconstruction from random projections, Inverse Problems and Imaging, 6(3), 547–563, 2012.

  • Bean San Goh, Zheng Peng, Cho Seng Lee, Junfeng Yang, and Min Kong, Approximate greatest descent method and quasi-Newton matrices in optimization, Dynamics of Continuous, Discrete and Impulsive Systems, Series B: Applications and Algorithms, 18(1), 17–28, 2011.  

  • Raymond H. Chan, Junfeng Yang, and Xiaoming Yuan, Alternating direction method for image inpainting in wavelet domains, SIAM Journal on Imaging Sciences, 4(3), 807–826, 2011.  

  • Junfeng Yang, and Yin Zhang, Alternating direction algorithms for L1-problems in compressive sensing, SIAM Journal on Scientific Computing, 33(1), 250–278, 2011. 

  • Wotao Yin, Simon Morgan, Junfeng Yang, and Yin Zhang, Practical compressive sensing with Toeplitz and circulant matrices, Proceedings of SPIE, 7744, 77440K (Volume title: Visual Communications and Image Processing), 2010.  

  • Junfeng Yang, Yin Zhang, and Wotao Yin, A fast alternating direction method for TVL1-L2 signal reconstruction from partial Fourier data, IEEE Journal of Selected Topics in Signal Processing (Special Issue on Compressive Sensing), 4(2), 288–297, 2010.  

  • Junfeng Yang, Yin Zhang, and Wotao Yin, An efficient TVL1 algorithm for deblurring multichannel images corrupted by impulsive noise, SIAM Journal on Scientific Computing, 31(4), 2842–2865, 2009.  

  • Junfeng Yang, Wotao Yin, Yin Zhang, and Yilun Wang, A fast algorithm for edge-preserving variational multichannel image restoration, SIAM Journal on Imaging Sciences, 2(2), 569–592, 2009.  

  • Bingsheng He, Xiang Wang, and Junfeng Yang, A comparison of different contraction methods for monotone variational inequalities, Journal of Computational Mathematics, 27(4), 459–473, 2009.

  • Junfeng Yang, Dynamic power price problem: an inverse variational inequality approach, Journal of Industrial and Management Optimization, 4(4), 673–684, 2008.  

  • Yilun Wang, Junfeng Yang, Wotao Yin, and Yin Zhang, A new alternating minimization algorithm for total variation image reconstruction, SIAM Journal on Imaging Sciences, 1(3), 248–272, 2008.

  • Junfeng Yang, Wotao Yin, Yin Zhang, and Yilun Wang, A class of fast algorithm for total variation image restoration, OpenStax CNX, vol. 1, pp. 4-7, 2008.

  • Raymond H. Chan, Shiqian Ma, and Junfeng Yang, Inertial primal dual algorithms for structured convex optimization, arXiv 1409.2992, 2014.

  • Min Tao, and Junfeng Yang, Alternating direction algorithms for total variation deconvolution in image reconstruction, Optimization Online, November 17, 2009; TR0918, Department of Mathematics, Nanjing University, 2009/11; Research rep., Rice University, 2009/11.

  • 闫喜红, 李浩, 王川龙, 陈红梅, 杨俊锋. 一种推广的求解可分离凸优化问题的黄金比率邻近ADMM算法, 《计算数学》, 第46卷, 第1期, 第1--16页, 2024.

  • 周丹青, 常小凯, 杨俊锋. 一类新的黄金比率原始对偶算法, 《高等学校计算数学学报》, 第44卷, 第1期, 第97--106页, 2022.

  • 顾国勇, 杨俊锋. 邻近点算法的精确次线性收敛率, 柚子优化, 2019.

  • 杨俊锋, 图像处理中全变差正则化数据拟合问题算法回顾, 《运筹学学报》, 第21卷, 第4期, 第69--83页, 2017.

  • 杨俊锋, 压缩感知与L1模交替方向解码算法，《科学观察》，第11卷，第6期，第47--51页，2016.