# Estimation of samples relevance by their histograms

## TL;DR

This paper discusses a method for estimating the relevance of samples based on their histograms using variational principles, including conditions for reducing the complexity of related linear programming problems.

## Contribution

It introduces a novel approach for relevance estimation of samples through histogram analysis and provides conditions for simplifying associated linear programming tasks.

## Key findings

- Relevance estimation can be effectively performed using histogram-based variational principles.
- Conditions for dimension reduction of linear programming problems are identified.
- The approach improves computational efficiency in relevance assessment.

## Abstract

The problem of the estimation of relevance to a set of histograms generated by samples of a discrete time process is discussed on the base of the variational principles proposed in the previous paper [1]. Some conditions for dimension reduction of corresponding linear programming problems are presented also.

---
Source: https://tomesphere.com/paper/1701.08383