In this paper, we first propose a novel generalized power iteration (GPI) method to solve the
quadratic problem on the Stiefel manifold (QPSM) as min_ W^ TW= I min WTW= I Tr (WT …

Feature selection has attracted a lot of attention in obtaining discriminative and non-
redundant features from high-dimension data. Compared with traditional filter and wrapper …

Due to lack of scale change in orthogonal least square regression (OLSR), the scaling term
is introduced to OLSR to build up a novel orthogonal least square regression with optimal …

Since brain network organization is essentially governed by the harmonic waves derived
from the Eigen-system of the underlying Laplacian matrix, discovering the harmonic-based …

We study semidefinite programming (SDP) relaxations for the NP-hard problem of globally
optimizing a quadratic function over the Stiefel manifold. We introduce a strengthened …

Linear programming on the Stiefel manifold (LPS) is studied for the first time. It aims at
minimizing a linear objective function over the set of all-tuples of orthonormal vectors in …

A sub‐Stiefel matrix is a matrix that results from deleting simultaneously the last row and the
last column of an orthogonal matrix. In this paper, we consider a Procrustes problem on the …

针对迭代量化哈希算法未考虑高维图像描述符中呈现出的自然矩阵结构, 当视觉描述符由高维
特征向量表示并且分配长二进制码时, 投影矩阵需要昂贵的空间和时间复杂度的问题 …

Quadratic optimization problems are crucial in various applications, ranging from
engineering and science to economics. However, solving nonconvex quadratic problems …

The Stackelberg prediction game (SPG) is an effective model that formulates the strategic
interaction between the learner and data generator in a competition situation in which the …