Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Federated Learning over Wireless IoT Networks with Optimized
  Communication and Resources   To leverage massive distributed data and computation resources, machine
learning in the network edge is considered to be a promising technique
especially for large-scale model training. Federated learning (FL), as a
paradigm of collaborative learning techniques, has obtained increasing research
attention with the benefits of communication efficiency and improved data
privacy. Due to the lossy communication channels and limited communication
resources (e.g., bandwidth and power), it is of interest to investigate fast
responding and accurate FL schemes over wireless systems. Hence, we investigate
the problem of jointly optimized communication efficiency and resources for FL
over wireless Internet of things (IoT) networks. To reduce complexity, we
divide the overall optimization problem into two sub-problems, i.e., the client
scheduling problem and the resource allocation problem. To reduce the
communication costs for FL in wireless IoT networks, a new client scheduling
policy is proposed by reusing stale local model parameters. To maximize
successful information exchange over networks, a Lagrange multiplier method is
first leveraged by decoupling variables including power variables, bandwidth
variables and transmission indicators. Then a linear-search based power and
bandwidth allocation method is developed. Given appropriate hyper-parameters,
we show that the proposed communication-efficient federated learning (CEFL)
framework converges at a strong linear rate. Through extensive experiments, it
is revealed that the proposed CEFL framework substantially boosts both the
communication efficiency and learning performance of both training loss and
test accuracy for FL over wireless IoT networks compared to a basic FL approach
with uniform resource allocation.

23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph