Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimality of Binning for Distributed Hypothesis Testing   We study a hypothesis testing problem in which data is compressed
distributively and sent to a detector that seeks to decide between two possible
distributions for the data. The aim is to characterize all achievable encoding
rates and exponents of the type 2 error probability when the type 1 error
probability is at most a fixed value. For related problems in distributed
source coding, schemes based on random binning perform well and often optimal.
For distributed hypothesis testing, however, the use of binning is hindered by
the fact that the overall error probability may be dominated by errors in
binning process. We show that despite this complication, binning is optimal for
a class of problems in which the goal is to "test against conditional
independence." We then use this optimality result to give an outer bound for a
more general class of instances of the problem.

16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org