Normal Cones Intersection Rule and Optimality Analysis for Low-Rank Matrix Optimization with Affine Manifolds

TL;DR

This paper develops a comprehensive optimality analysis framework for low-rank matrix optimization problems constrained by affine manifolds, including intersection rules, stationarity concepts, and second-order conditions.

Contribution

It introduces the intersection rule of Fréchet normal cones and characterizes various stationary points, advancing the theoretical understanding of low-rank matrix optimization.

Findings

Explicit formulas for normal cones are derived.

First-order optimality conditions for stationary points are established.

Second-order necessary and sufficient conditions are proposed.

Abstract

The low-rank matrix optimization with affine manifold (rank-MOA) aims to minimize a continuously differentiable function over a low-rank set intersecting with an affine manifold. This paper is devoted to the optimality analysis for rank-MOA. As a cornerstone, the intersection rule of the Fr\'{e}chet normal cone to the feasible set of the rank-MOA is established under some mild linear independence assumptions. Aided with the resulting explicit formulae of the underlying normal cone, the so-called F-stationary point and the \alpha-stationary point of rank-MOA are investigated and the relationship with local/global minimizers are then revealed in terms of first-order optimality conditions. Furthermore, the second-order optimality analysis, including the necessary and the sufficient conditions, is proposed based on the second-order differentiation information of the model. All these results will enrich the theory of low-rank matrix optimization and give potential clues to designing efficient numerical algorithms for seeking low rank solutions. Meanwhile, two specific applications of the rank-MOA are discussed to illustrate our proposed optimality analysis.