Convexification with Bounded Gap for Randomly Projected Quadratic Optimization
From MaRDI portal
Publication:5080508
DOI10.1137/21M1433678zbMath1493.90122arXiv2107.05272OpenAlexW4298096160MaRDI QIDQ5080508
Pierre-Louis Poirion, Terunari Fuji, Akiko Takeda
Publication date: 31 May 2022
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2107.05272
Related Items (2)
Random projection preserves stability with high probability ⋮ Stable probability of reduced matrix obtained by Gaussian random projection
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Concentration inequalities and moment bounds for sample covariance operators
- Support vector machine classification with indefinite kernels
- A trace inequality of John von Neumann
- Sketching meets random projection in the dual: a provable recovery algorithm for big and high-dimensional data
- Dimensionality reduction of SDPs through sketching
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- Support-vector networks
- Random projections for quadratic programs
- CVXPY: A Python-Embedded Modeling Language for Convex Optimization
- Computational Advertising: Techniques for Targeting Relevant Ads
- Randomized Sketches of Convex Programs With Sharp Guarantees
- Randomized Algorithms for Matrices and Data
- Extensions of Lipschitz mappings into a Hilbert space
- High-Dimensional Probability
- Semidefinite Programming
- Determinantal Point Processes in Randomized Numerical Linear Algebra
- Random Projections for Linear Programming
- An Introduction to Matrix Concentration Inequalities
This page was built for publication: Convexification with Bounded Gap for Randomly Projected Quadratic Optimization
