S. Theodoridis, Machine Learning: A Bayesian and Optimization Perspective, 1st ed. Academic Press, 2015.
A. Beck and M. Teboulle, "A Fast Iterative Shrinkage-Thresholding Algorithm, " Society for Industrial and Applied Mathematics Journal on Imaging Sciences, vol. 2, no. 1, pp. 183-202, 2009.
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.
S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, "Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, " Foundations and Trends in Machine Learning, vol. 3, no. 1, 2010.
N. Parikh and S. Boyd, "Proximal Algorithms, " Foundations and Trends in Optimization, vol. 1, no. 3, pp. 127-239, 2014.
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.
Z. Yang, Z. Wang, H. Liu, Y. C. Eldar, and T. Zhang, "Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference, " in International Conference on Machine Learning (ICML), 2016.
J. Fan and R. Li, "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties, " Journal of the American Statistical Association, vol. 96, no. 456, pp. 1348-1360, dec 2001.
E. J. Candès, M. B. Wakin, and S. P. Boyd, "Enhancing Sparsity by Reweighted L1 Minimization, " Journal of Fourier Analysis and Applications, vol. 14, no. 5-6, pp. 877-905, dec 2008.
T. Zhang, "Analysis of Multi-stage Convex Relaxation for Sparse Regularization, " Journal of Machine Learning Research, vol. 11, pp. 1081- 1107, 2010.
J. Weston, A. Elisseeff, B. Scholkopf, and M. Tipping, "The use of zero-norm with linear models and kernel methods, " Journal of Machine Learning Research, vol. 3, pp. 1439-1461, 2003.
G. Gasso, A. Rakotomamonjy, and S. Canu, "Recovering sparse signals with a certain family of nonconvex penalties and DC programming, " IEEE Transactions on Signal Processing, vol. 57, no. 12, pp. 4686- 4698, dec 2009.
P. Gong, C. Zhang, Z. Lu, J. Huang, and J. Ye, "A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems, " in Proceedings of the 30th International Conference on Machine Learning, 2013, pp. 37-45.
Y. Yang, M. Pesavento, S. Chatzinotas, and B. Ottersten, "Successive convex approximation algorithms for sparse signal estimation with nonconvex regularizations, " 2018, technical report.[Online]. Available: http://orbilu.uni.lu/handle/10993/35100.
J. M. Ortega and W. C. Rheinboldt, Iterative solution of nonlinear equations in several variables. Academic, New York, 1970.
S. M. Robinson and R. H. Day, "A sufficient condition for continuity of optimal sets in mathematical programming, " Journal of Mathematical Analysis and Applications, vol. 45, no. 2, pp. 506-511, feb 1974.
G. Scutari, F. Facchinei, P. Song, D. P. Palomar, and J.-S. Pang, "Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems, " IEEE Transactions on Signal Processing, vol. 62, no. 3, pp. 641-656, feb 2014.
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.
S. Wright, R. Nowak, and M. Figueiredo, "Sparse Reconstruction by Separable Approximation, " IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2479-2493, jul 2009.