PreprintCC BY 4.0HAL
Conditional Infimum, Hidden Convexity and S-Procedure
Abstract
Detecting hidden convexity is one of the tools to address nonconvex minimization problems, and find global minimizers. We introduce the notion of conditional infimum, develop the theory, and establish a tower property, relevant for minimization problems. Then, we illustrate how the conditional infimum is instrumental in revealing hidden convexity. Thus equipped, we provide a new sufficient condition for hidden convexity in nonconvex quadratic minimization problems, that encompasses and goes beyond known results (with the notion of block-signed pair matrix-vector). We also show how the conditional infimum is especially adapted to tackle the so-called S-procedure.
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BibTeX
@misc{chancelier2026conditional,
title = {{Conditional Infimum, Hidden Convexity and S-Procedure}},
author = {Jean-Philippe Chancelier and Michel de Lara},
howpublished = {HAL},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.24661},
eprint = {2609.24661},
archivePrefix = {arXiv},
url = {https://hal.science/hal-05754640v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Conditional Infimum, Hidden Convexity and S-Procedure
AU - Jean-Philippe Chancelier
AU - Michel de Lara
PY - 2026
DA - 2026/09/18
PB - HAL
DO - 10.48550/arxiv.2609.24661
UR - https://hal.science/hal-05754640v1
AB - Detecting hidden convexity is one of the tools to address nonconvex minimization problems, and find global minimizers. We introduce the notion of conditional infimum, develop the theory, and establish a tower property, relevant for minimization problems. Then, we illustrate how the conditional infimum is instrumental in revealing hidden convexity. Thus equipped, we provide a new sufficient condition for hidden convexity in nonconvex quadratic minimization problems, that encompasses and goes beyond known results (with the notion of block-signed pair matrix-vector). We also show how the conditional infimum is especially adapted to tackle the so-called S-procedure.
ER -