Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning mixtures of spherical Gaussians: moment methods and spectral
  decompositions   This work provides a computationally efficient and statistically consistent
moment-based estimator for mixtures of spherical Gaussians. Under the condition
that component means are in general position, a simple spectral decomposition
technique yields consistent parameter estimates from low-order observable
moments, without additional minimum separation assumptions needed by previous
computationally efficient estimation procedures. Thus computational and
information-theoretic barriers to efficient estimation in mixture models are
precluded when the mixture components have means in general position and
spherical covariances. Some connections are made to estimation problems related
to independent component analysis.

23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc