Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Compressed Gradient Tracking for Decentralized Optimization Over General
  Directed Networks   In this paper, we propose two communication efficient decentralized
optimization algorithms over a general directed multi-agent network. The first
algorithm, termed Compressed Push-Pull (CPP), combines the gradient tracking
Push-Pull method with communication compression. We show that CPP is applicable
to a general class of unbiased compression operators and achieves linear
convergence rate for strongly convex and smooth objective functions. The second
algorithm is a broadcast-like version of CPP (B-CPP), and it also achieves
linear convergence rate under the same conditions on the objective functions.
B-CPP can be applied in an asynchronous broadcast setting and further reduce
communication costs compared to CPP. Numerical experiments complement the
theoretical analysis and confirm the effectiveness of the proposed methods.

29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex