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Kernel methods in system identification, machine learning and function estimation: A survey

Overview of attention for article published in Automatica, March 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user
facebook
1 Facebook page
q&a
1 Q&A thread

Citations

dimensions_citation
577 Dimensions

Readers on

mendeley
491 Mendeley
citeulike
1 CiteULike
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Title
Kernel methods in system identification, machine learning and function estimation: A survey
Published in
Automatica, March 2014
DOI 10.1016/j.automatica.2014.01.001
Authors

Gianluigi Pillonetto, Francesco Dinuzzo, Tianshi Chen, Giuseppe De Nicolao, Lennart Ljung

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 491 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 3 <1%
Switzerland 2 <1%
Germany 2 <1%
Czechia 2 <1%
United States 2 <1%
United Kingdom 2 <1%
France 1 <1%
Canada 1 <1%
Mexico 1 <1%
Other 5 1%
Unknown 470 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 161 33%
Student > Master 74 15%
Researcher 56 11%
Professor 22 4%
Student > Doctoral Student 20 4%
Other 83 17%
Unknown 75 15%
Readers by discipline Count As %
Engineering 262 53%
Computer Science 55 11%
Mathematics 19 4%
Agricultural and Biological Sciences 11 2%
Chemical Engineering 8 2%
Other 36 7%
Unknown 100 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 02 February 2021.
All research outputs
#8,262,107
of 25,374,647 outputs
Outputs from Automatica
#137
of 1,096 outputs
Outputs of similar age
#76,245
of 236,361 outputs
Outputs of similar age from Automatica
#5
of 10 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1,096 research outputs from this source. They receive a mean Attention Score of 2.4. This one has done well, scoring higher than 86% 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 236,361 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.