Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Approximate Recovery in Changepoint Problems, from $\ell_2$ Estimation
  Error Rates   In the 1-dimensional multiple changepoint detection problem, we prove that
any procedure with a fast enough $\ell_2$ error rate, in terms of its
estimation of the underlying piecewise constant mean vector, automatically has
an (approximate) changepoint screening property---specifically, each true jump
in the underlying mean vector has an estimated jump nearby. We also show, again
assuming only knowledge of the $\ell_2$ error rate, that a simple
post-processing step can be used to eliminate spurious estimated changepoints,
and thus delivers an (approximate) changepoint recovery
property---specifically, in addition to the screening property described above,
we are assured that each estimated jump has a true jump nearby. As a special
case, we focus on the application of these results to the 1-dimensional fused
lasso, i.e., 1-dimensional total variation denoising, and compare the
implications with existing results from the literature. We also study
extensions to related problems, such as changepoint detection over graphs.

13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
1
The categories of this paper are: cs
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn