Bayesian compressive sensing and projection optimization

Shihao Ji, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations


This paper introduces a new problem for which machine-learning tools may make an impact. The problem considered is termed "compressive sensing", in which a real signal of dimension N is measured accurately based on K
Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
Number of pages8
StatePublished - Aug 23 2007
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2021-02-09


Dive into the research topics of 'Bayesian compressive sensing and projection optimization'. Together they form a unique fingerprint.

Cite this