Mathematical optimization is an important branch of applied mathematics. Different classes
of optimization problems are categorized based on their problem structures. While there are …

In this paper, based on the Riemannian optimization approach we propose a Riemannian
nonlinear conjugate gradient method with nonmonotone line search technique for solving …

Nowadays, audio–visual automatic speech recognition (AV-ASR) is an emerging field of
research, but there is still lack of proper visual features for visual speech recognition. Visual …

In this paper, we propose a manifold optimization empowered two-timescale channel
estimation (MO-TTCE) scheme for reconfigurable intelligent surface (RIS)-assisted multiuser …

In this paper, a Riemannian conjugate gradient method for a Riemannian optimization
problem related to the singular value decomposition of a complex matrix is developed. The …

This paper focuses on algorithms for the truncated Takagi factorization of complex symmetric
matrices. The problem is formulated as a Riemannian optimization problem on a complex …

Optimization problems on the generalized Stiefel manifold (and products of it) are prevalent
across science and engineering. For example, in computational science they arise in …

The l parameterized generalized eigenvalue problems for the nonsquare matrix pencils,
proposed by Chu et al. in 2006, can be formulated as an optimization problem on a …

The truncated singular value decomposition has been widely used in many areas of science
including engineering, and statistics, etc. In this paper, the original truncated complex …

With the increasing demand for security in many fastest growing applications, biometric
recognition is the most prominent authentication system. User authentication through …