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Ternary Compression for Communication-Efficient Federated Learning

Overview of attention for article published in IEEE Transactions on Neural Networks and Learning Systems, February 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
twitter
7 X users
patent
3 patents

Readers on

mendeley
122 Mendeley
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Article details
Title
Ternary Compression for Communication-Efficient Federated Learning
Published in
IEEE Transactions on Neural Networks and Learning Systems, February 2022
DOI 10.1109/tnnls.2020.3041185
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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Activity
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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 122 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 14 11%
Student > Ph. D. Student 12 10%
Other 5 4%
Lecturer 5 4%
Student > Doctoral Student 5 4%
Other 13 11%
Unknown 68 56%
Readers by discipline
Readers by discipline Count As %
Computer Science 29 24%
Engineering 13 11%
Medicine and Dentistry 3 2%
Business, Management and Accounting 2 2%
Unspecified 1 <1%
Other 5 4%
Unknown 69 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 November 2025.
All research outputs
#2,527,659
of 32,452,905 outputs
Outputs from IEEE Transactions on Neural Networks and Learning Systems
#52
of 2,940 outputs
Outputs of similar age
#48,523
of 468,926 outputs
Outputs of similar age from IEEE Transactions on Neural Networks and Learning Systems
#4
of 33 outputs
Altmetric has tracked 32,452,905 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,940 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 468,926 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.