Nonconvex Optimization

Accelerated First-Order Optimization Algorithms for Machine Learning

Numerical optimization serves as one of the pillars of machine learning. To meet the demands of big data applications, lots of efforts have been done on designing theoretically and practically fast algorithms. This paper provides a comprehensive …

On the Convergence of Learning-based Iterative Methods for Nonconvex Inverse Problems

Numerous tasks at the core of statistics, learning and vision areas are specific cases of ill-posed inverse problems. Recently, learning-based (e.g., deep) iterative methods have been empirically shown to be useful for these problems. Nevertheless, …

Generalized Nonconvex Nonsmooth Low-Rank Minimization

In this work, the nonconvex surrogate functions of L_0-norm are extended on the singular values to approximate the rank function. It is observed that all the existing nonconvex surrogate functions are concave and monotonically increasing on [0, \infty). Then a general solver IRNN is proposed.