ABSTRACT. Compressive sampling (CS), or Compressed Sensing, has generated a tremendous amount of excitement in the signal processing com- munity.
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This paper compares the theoretical performance of compressive and adaptive sampling in noisy conditions, and it is shown that for certain classes of piecewise ...
This paper compares the theoretical performance of compressive and adaptive sampling in noisy conditions, and it is shown that for certain classes of piecewise ...
Compressed Sensing Vs. Active Learning | IEEE Conference ...
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Adaptive sampling (AS), also called Active Learning, uses information gleaned from previous observations (e.g., feedback) to focus the sampling process.
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Oct 9, 2017 · The idea behind compressed sensing is that a sparse signal can be recovered from very few linear measurements. In symbols, if x is N×1 ...
Adaptive sampling (AS), also called Active Learning, uses information gleaned from previous observations (e.g., feedback) to focus the sampling process.
Jul 11, 2013 · Can you explain compressive sensing in a few words from a machine learning perspective?
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Missing: Compressed Sensing
sign in. Inproceedings,. Compressed Sensing Vs. Active Learning. R. Castro, J. Haupt, and R. Nowak. ICASSP (3), page 820-823. IEEE, (2006 ). 1. 1. Meta data.