Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: When compressive learning fails: blame the decoder or the sketch?   In compressive learning, a mixture model (a set of centroids or a Gaussian
mixture) is learned from a sketch vector, that serves as a highly compressed
representation of the dataset. This requires solving a non-convex optimization
problem, hence in practice approximate heuristics (such as CLOMPR) are used. In
this work we explore, by numerical simulations, properties of this non-convex
optimization landscape and those heuristics.

14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex