Random projections for semidefinite programming * - Archive ouverte HAL
Communication Dans Un Congrès Année : 2022

Random projections for semidefinite programming *

Résumé

Random projections can reduce the dimensionality of point sets while keeping approximate congruence. Applying random projections to optimization problems raises many theoretical and computational issues. Most of the theoretical issues in the application of random projections to conic programming were addressed in [1]. This paper focuses on semidefinite programming.
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Dates et versions

hal-03795941 , version 1 (04-10-2022)

Identifiants

  • HAL Id : hal-03795941 , version 1

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Leo Liberti, Benedetto Manca, Antoine Oustry, Pierre-Louis Poirion. Random projections for semidefinite programming *. AIRO-ODS 2022, Aug 2022, Florence, Italy. ⟨hal-03795941⟩
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