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- W3216039123 abstract "Rank and cardinality penalties are hard to handle in optimization frameworks due to non-convexity and discontinuity. Strong approximations have been a subject of intense study and numerous formulations have been proposed. Most of these can be described as separable, meaning that they apply a penalty to each element (or singular value) based on size, without considering the joint distribution. In this paper we present a class of non-separable penalties and give a recipe for computing strong relaxations suitable for optimization. In our analysis of this formulation we first give conditions that ensure that the global ly optimal solution of the relaxation is the same as that of the original (unrelaxed) objective. We then show how a stationary point can be guaranteed to be unique under the restricted isometry property (RIP) assumption. <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sup>" @default.
- W3216039123 created "2021-12-06" @default.
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- W3216039123 date "2021-10-01" @default.
- W3216039123 modified "2023-09-23" @default.
- W3216039123 title "Relaxations for Non-Separable Cardinality/Rank Penalties" @default.
- W3216039123 doi "https://doi.org/10.1109/iccvw54120.2021.00023" @default.
- W3216039123 hasPublicationYear "2021" @default.
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