Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Regression Approach to Certain Information Transmission Problems   A general information transmission model, under independent and identically
distributed Gaussian codebook and nearest neighbor decoding rule with processed
channel output, is investigated using the performance metric of generalized
mutual information. When the encoder and the decoder know the statistical
channel model, it is found that the optimal channel output processing function
is the conditional expectation operator, thus hinting a potential role of
regression, a classical topic in machine learning, for this model. Without
utilizing the statistical channel model, a problem formulation inspired by
machine learning principles is established, with suitable performance metrics
introduced. A data-driven inference algorithm is proposed to solve the problem,
and the effectiveness of the algorithm is validated via numerical experiments.
Extensions to more general information transmission models are also discussed.

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The categories of this paper are: physics
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
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The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph