Z. Yang, Z. Wang, H. Liu, Y. C. Eldar, and T. Zhang, “Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference,” 2016, in Proc. International Conference on Machine Learning (ICML). [Online]. Available: http://proceedings.mlr.press/v48/yangc16.pdf
Y. Yang and M. Pesavento, “A Unified Successive Pseudoconvex Approximation Framework,” IEEE Transactions on Signal Processing, vol. 65, no. 13, pp. 3313-3328, Jul. 2017.
M. Razaviyayn, M. Hong, and Z.-Q. Luo, “A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization,” SIAM Journal on Optimization, vol. 23, no. 2, pp. 1126-1153, Jan. 2013.
M. Razaviyayn, M. Hong, Z.-Q. Luo, and J.-S. Pang, “Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization,” in Proceedings of the 27th International Conference on Neural Information Processing Systems, 2014, pp. 1440-1448.
F. Facchinei, G. Scutari, and S. Sagratella, “Parallel Selective Algorithms for Nonconvex Big Data Optimization,” IEEE Transactions on Signal Processing, vol. 63, no. 7, pp. 1874-1889, Nov. 2015.
K. Slavakis, G. B. Giannakis, and G. Mateos, “Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge,” IEEE Signal Processing Magazine, vol. 31, no. 5, pp. 18-31, Sep. 2014.
Y. Yang and M. Pesavento, “A parallel best-response algorithm with exact line search for nonconvex sparsity-regularized rank minimization,” Apr. 2018, to appear in Proc. ICASSP. [Online]. Available: http://orbilu.uni.lu/handle/10993/33772
D. P. Bertsekas, Nonlinear programming. Athena Scientific, 1999.
P. Tseng, “Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization,” Journal of Optimization Theory and Applications, vol. 109, no. 3, pp. 475-494, Jun. 2001.
C. Berge, Topological Spaces: Including a Treatment of Multi-Valued Functions, Vector Spaces and Convexity. Dover Publications, 1997.