Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sparsity-Aware Learning and Compressed Sensing: An Overview   This paper is based on a chapter of a new book on Machine Learning, by the
first and third author, which is currently under preparation. We provide an
overview of the major theoretical advances as well as the main trends in
algorithmic developments in the area of sparsity-aware learning and compressed
sensing. Both batch processing and online processing techniques are considered.
A case study in the context of time-frequency analysis of signals is also
presented. Our intent is to update this review from time to time, since this is
a very hot research area with a momentum and speed that is sometimes difficult
to follow up.

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The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
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The categories of this paper are: dg-ga