A theoretical guarantee for data completion via geometric separation

Emily J. King; James M. Murphy

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arXiv · 1705.10745

A theoretical guarantee for data completion via geometric separation

Emily J. King·James M. Murphy

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Abstract

Scientific and commercial data is often incomplete. Recovery of the missing information is an important pre-processing step in data analysis. Real-world data can in many cases be represented as a superposition of two or more different types of structures. For example, images may often be decomposed into texture and cartoon-like components. When incomplete data comes from a distribution well-represented as a mixture of different structures, a sparsity-based method combining concepts from data completion and data separation can successfully recover the missing data. This short note presents a theoretical guarantee for success of the combined separation and completion approach which generalizes proofs from the distinct problems.

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Emily J. King, James M. Murphy. 2017-05-30. A theoretical guarantee for data completion via geometric separation. https://arxiv.org/abs/1705.10745

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