Google scholar citations


  • T. Su, Y. Sun, Y. Xu and W. Yin. Markov Chain Block coordinate descent. Submitted, 2018. [arXiv]

  • X. Gao, Y. Xu and S. Zhang. Randomized primal-dual proximal block coordinate updates. Accepted in Journal of the Operations Research Society of China, 2018. [arXiv]

  • Y. Ouyang and Y. Xu. Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems. Submitted, 2018. [arXiv]

  • Y. Xu. Primal-dual stochastic gradient method for convex programs with many functional constraints. Submitted, 2018. [arXiv]

  • Y. Xu. First-order methods for constrained convex programming based on linearized augmented Lagrangian function. Submitted, 2017. [arXiv]

  • Y. Xu. Iteration complexity of inexact augmented Lagrangian methods for constrained convex programming. Submitted, 2017. [arXiv]

  • H. Shi, S. Tu, Y. Xu and W. Yin. A Primer on Coordinate Descent Algorithms, 2016. [arXiv]

  • J. Shi, Y. Xu and R. Baraniuk. Sparse bilinear logistic regression, 2014. [arXiv]


  • Y. Xu. Asynchronous parallel primal-dual block coordinate update methods for affinely constrained convex programs. Computational Optimization and Applications, 72(1), pp. 87–113, 2019. [arXiv] [Slides]

  • N. Zhou, Y. Xu, H. Chen, Z. Yuan and B. Chen. Maximum Correntropy Criterion based Sparse Subspace Learning for Unsupervised Feature Selection. IEEE Transactions on Circuits and Systems for Video Technology, 29(2), pp. 404–417, 2019.


  • D. Oliveira, H. Wolkowicz and Y. Xu. ADMM for the SDP relaxation of the QAP. Mathematical Programming Computation, 10(4), pp. 631–658, 2018. [code] [arXiv]

  • B. Liu, T. Xie, Y. Xu, M. Ghavamzadeh, Y. Chow, D. Lyu and D. Yoon. A Block Coordinate Ascent Algorithm for Mean-Variance Optimization, NeurIPS, pp. 1073–1083, 2018.

  • X. Li, J. Ren, S. Rambhatla, Y. Xu and J. Haupt. Robust PCA via dictionary based outlier pursuit, ICASSP, pp. 4699–4703, 2018.

  • Y. Xu. Hybrid Jacobian and Gauss-Seidel proximal block coordinate update methods for linearly constrained convex programming. SIAM Journal on Optimization, 28(1), pp. 646–670, 2018. [pdf]

  • Y. Chen, J. Zhang and Y. Xu. Adaptive lasso for accelerated hazards models. Journal of Statistical Computation and Simulation, 88(15), pp. 2948–2960, 2018.

  • Y. Xu and S. Zhang. Accelerated Primal-Dual Proximal Block Coordinate Updating Methods for Constrained Convex Optimization. Computational Optimization and Applications, 70(1), 91–128, 2018. [arXiv]

  • Y. Xu. On the convergence of higher-order orthogonality iteration. Linear and Multilinear Algebra, 66(11), pp. 2247–2265, 2018. [arXiv] [Slides]

  • F. Wen and Y. Xu. HOSVD Based Multidimensional Parameter Estimation for Massive MIMO System from Incomplete Channel Measurements. Multidimensional Systems and Signal Processing, 29(4), pp. 1255–1267, 2018.


  • Z. Peng, Y. Xu, M. Yan and W. Yin. On the Convergence of Asynchronous Parallel Iteration with Unbounded Delays. Special issue on Journal of the Operations Research Society of China, 2017. [arXiv]

  • Y. Xu. Accelerated first-order primal-dual proximal methods for linearly constrained composite convex programming. SIAM Journal on Optimization, 27(3), 1459–1484, 2017. [pdf]

  • Y. Xu and W. Yin. A globally convergent algorithm for nonconvex optimization based on block coordinate update. Journal of Scientific Computing, 72(2), 700–734, 2017. [arXiv]

  • Y. Xu. Fast algorithms for higher-order singular value decomposition from incomplete data. Journal of Computational Mathematics, Special Issues on Optimization and Structured Solution, 35(4), 395–420, 2017. [arXiv] [code]


  • Z. Peng, Y. Xu, M. Yan and W. Yin. ARock: an algorithmic framework for asynchronous parallel coordinate updates. SIAM Journal on Scientific Computing, 38(5), A2851–A2879, 2016. [arXiv] [code]

  • Z. Peng, T. Wu, Y. Xu, M. Yan and W. Yin. Coordinate Friendly Structures, Algorithms and applications. Annals of Mathematical Sciences and Applications, 1(1), pp. 57–119, 2016. [arXiv]

  • Y. Xu and W. Yin. A fast patch-dictionary method for whole image recovery. Inverse Problems and Imaging, 10(2), 563–583, 2016. [code] [arXiv]

  • N. Zhou, Y. Xu, H. Cheng, J. Fang and W. Pedrycz. Global and local structure preserving sparse subspace learning: an iterative approach to unsupervised feature selection. Pattern Recognition, 53, pp. 87–101, 2016. [arXiv]


  • Y. Xu and W. Yin. Block stochastic gradient iteration for convex and nonconvex optimization. SIAM Journal on Optimization, 25(3), 1686–1716, 2015. [pdf] [demo] [Slides]

  • Y. Xu, R. Hao, W. Yin and Z. Su. Parallel matrix factorization for low-rank tensor completion. Inverse Problems and Imaging, 9(2), 601–624, 2015. [pdf] [code]

  • Y. Xu. Alternating proximal gradient method for sparse nonnegative Tucker decomposition. Mathematical Programming Computation, 7(1), 39–70, 2015. [code]

  • Y. Xu, I. Akrotirianakis and A. Chakraborty. Proximal gradient method for huberized support vector machine, Pattern Analysis and Applications, 19(4), 989–1005, 2015. [pdf]

  • Y. Xu, I. Akrotirianakis and A. Chakraborty. Alternating direction method of multipliers for regularized multiclass support vector machines. International Workshop on Machine Learning, Optimization and Big Data, 105–117, 2015. [arXiv]

2014 and earlier

  • Y. Xu, W. Yin and S. Osher. Learning circulant sensing kernels. Inverse Problems and Imaging 8(3), 901–923, 2014. [pdf][code]

  • Y. Xu and W. Yin. A block coordinate descent method for regularized multi-convex optimization with applications to nonnegative tensor factorization and completion. SIAM Journal on imaging sciences, 6(3), pp. 1758–1789, 2013. [code]

  • M. Lai, Y. Xu and W. Yin. Improved iteratively reweighted least squares for unconstrained smoothed Lq minimization. SIAM Journal on Numerical Analysis, 51(2), pp. 927–957, 2013. [code]

  • Q. Ling, Y. Xu, W. Yin and Z. Wen. Distributed low-rank matrix completion. (ICASSP), pp. 2925–2928, 2012.

  • Y. Xu and J. Cui. Multitask n-Vehicle Exploration Problem: complexity and algorithms. Journal of Systems Science and Complexity, pp. 1080–1092, 2012.

  • Y. Xu, W. Yin, Z. Wen and Y. Zhang. An alternating direction algorithm for matrix completion with nonnegative factors. Journal of Frontiers of Mathematics in China, Special Issues on Computational Mathematics (Springer), pp. 365–384, 2011. [code] [arXiv]