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PreprintCC BY 4.0arXiv

On Completely Positive and Semidefinite Programs for Moment Bounds on Maximum of Random Quadratics

  • Buse Unluturk
  • Divya Padmanabhan
  • Karthik Natarajan
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Abstract

Completely positive programs are known to provide an exact representation to several NP-hard optimization problems. In this work, we look at the maximum of random quadratic functions and compute the maximum expected value over ambiguity sets defined with moment and support information. We propose exact completely positive programs and semidefinite programs when the random variables are Bernoulli, nonnegative and unrestricted in support. Our experimental study demonstrates the utility of these formulations.

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Cite

BibTeXRIS
BibTeX
@misc{unluturk2026completely,
  title = {{On Completely Positive and Semidefinite Programs for Moment Bounds on Maximum of Random Quadratics}},
  author = {Buse Unluturk and Divya Padmanabhan and Karthik Natarajan},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.19684},
  eprint = {2610.19684},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.19684},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - On Completely Positive and Semidefinite Programs for Moment Bounds on Maximum of Random Quadratics
AU  - Buse Unluturk
AU  - Divya Padmanabhan
AU  - Karthik Natarajan
PY  - 2026
DA  - 2026/10/14
PB  - arXiv
DO  - 10.48550/arxiv.2610.19684
UR  - https://arxiv.org/abs/2610.19684
AB  - Completely positive programs are known to provide an exact representation to several NP-hard optimization problems. In this work, we look at the maximum of random quadratic functions and compute the maximum expected value over ambiguity sets defined with moment and support information. We propose exact completely positive programs and semidefinite programs when the random variables are Bernoulli, nonnegative and unrestricted in support. Our experimental study demonstrates the utility of these formulations.
ER  -