Abstract
We discuss the application of random projections to conic programming: notably linear, second-order and semidefinite programs. We prove general approximation results on feasibility and optimality using the framework of formally real Jordan algebras. We then discuss some computational experiments on randomly generated semidefinite programs in order to illustrate the practical applicability of our ideas.
| Original language | English |
|---|---|
| Pages (from-to) | 204-220 |
| Number of pages | 17 |
| Journal | Linear Algebra and Its Applications |
| Volume | 626 |
| DOIs | |
| Publication status | Published - 1 Oct 2021 |
Keywords
- Approximation
- Johnson-Lindenstrauss lemma
- Jordan algebra
- Mathematical programming
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