# A First-Order Algorithm for the A-Optimal Experimental Design Problem: A Mathematical Programming Approach

arXiv: https://arxiv.org/abs/1311.2335 · HTML: https://mlsanity.com/paper/1311.2335/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Nov 2013.

## Built on by (most cited first, 1 of 1)

- [Subdata Selection for Measurement-Constrained Linear Regression under Model Misspecification](https://mlsanity.com/paper/2610.19351/) (2026)

## Abstract (arXiv)

We develop and analyse a first-order algorithm for the A-optimal experimental design problem. The problem is first presented as a special case of a parametric family of optimal design problems for which duality results and optimality conditions are given. Then, two first-order (Frank-Wolfe type) algorithms are presented, accompanied by a detailed time-complexity analysis of the algorithms and computational results on various sized problems.