On the calculation of upper variance under multiple probabilities

TL;DR

This paper introduces a straightforward algorithm to exactly compute the upper variance under multiple probabilities, addressing a minimax optimization problem and applying it to quadratic programming representations.

Contribution

It presents a novel, simple algorithm for solving the upper variance minimax problem exactly, with applications to quadratic programming.

Findings

Algorithm efficiently computes upper variance under multiple probabilities.

Provides probabilistic representation for certain quadratic programming problems.

Demonstrates the practical applicability of the algorithm.

Abstract

The notion of upper variance under multiple probabilities is defined by a corresponding minimax optimization problem. This paper proposes a simple algorithm to solve the related minimax optimization problem exactly. As an application, we provide the probabilistic representation for a class of quadratic programming problems.