Experimental Design Using Interlacing Polynomials
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Abstract (arXiv)
We present a unified deterministic approach for experimental design problems using the method of interlacing polynomials. Our framework recovers the best-known approximation guarantees for the well-studied D/A/E-design problems with simple analysis. Furthermore, we obtain improved non-trivial approximation guarantee for E-design in the challenging small budget regime. Additionally, our approach provides an optimal approximation guarantee for a generalized ratio objective that generalizes both D-design and A-design.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 14 references that are in the map. First posted on arXiv 15 Oct 2024.
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References · 7
- 2017Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approachcited by 19
- 2018Proportional Volume Sampling and Approximation Algorithms for A-Optimal Designcited by 7
- 2018Approximation Algorithms for D-optimal Designcited by 7
- 2014On largest volume simplices and sub-determinantscited by 6
- 2020A Spectral Approach to Network Designcited by 2
- 2020A Local Search Framework for Experimental Designcited by 2
- 2023Experimental Design for Any p-Normcited by 1
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