论文标题
真正的密度估计预测
Bona fide Riesz projections for density estimation
论文作者
论文摘要
样品测量在常规网格上以基础表示的重建空间的投影是一种强大而简单的方法，可以估算概率密度函数。在本文中，我们专注于Riesz基地，并提出了一个投影操作员，与以前的作品相比，该投影运营商保证了估算的真正属性，即非负性和总概率质量$ 1 $。我们的善意投影定义为凸问题。我们提出解决方案技术并评估它们。结果表明表现的改善，特别是在容易发生涟漪效应的情况下。
The projection of sample measurements onto a reconstruction space represented by a basis on a regular grid is a powerful and simple approach to estimate a probability density function. In this paper, we focus on Riesz bases and propose a projection operator that, in contrast to previous works, guarantees the bona fide properties for the estimate, namely, non-negativity and total probability mass $1$. Our bona fide projection is defined as a convex problem. We propose solution techniques and evaluate them. Results suggest an improved performance, specifically in circumstances prone to rippling effects.
