Quadratic discriminant analysis (QDA) is a widely used statistical tool to classify
observations from different multivariate Normal populations. The generalized quadratic …

Sparse Discriminant Analysis (SDA) has been widely used to improve the performance of
classical Fisher's Linear Discriminant Analysis in supervised metric learning, feature …

Abstract Linear Discriminant Analysis (LDA) is a well-known technique for feature extraction
and dimension reduction. The performance of classical LDA however, significantly degrades …

We consider in this work small random perturbations of a nonlinear oscillator with friction–
type dissipation. We rigorously prove that under non–degenerate perturbations of …

摘要传统基于分类学习的监督哈希方法并不能完全满足哈希检索技术需求, 但是线性判别分析却
能够在一定程度上做到这一点. 本文提出将线性判别分析作为深度网络的优化目标 …

In this paper, we explore advanced algorithmic frameworks for addressing the challenges in
non-convex optimization. We introduce inertial dynamical systems equipped with explicit …

Stochastic Gradient Langevin Dynamics (SGLD) have been widely used for Bayesian
sampling from certain probability distributions, incorporating derivatives of the log-posterior …

In this paper, we analysed classification rules under Bayesian decision theory. The setup we
considered here is fairly general, which can represent all possible parametric models. The …

We study the convergence behavior of a stochastic heavy-ball method with a small stepsize.
Under a change of time scale, we approximate the discrete scheme by a stochastic …