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Using neural networks to solve linear bilevel problems with unknown lower level

Overview of attention for article published in Optimization Letters, February 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Using neural networks to solve linear bilevel problems with unknown lower level
Published in
Optimization Letters, February 2023
DOI 10.1007/s11590-022-01958-7
Authors

Ioana Molan, Martin Schmidt

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Student > Doctoral Student 1 14%
Researcher 1 14%
Student > Ph. D. Student 1 14%
Unknown 2 29%
Readers by discipline Count As %
Mathematics 3 43%
Chemical Engineering 1 14%
Unknown 3 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 February 2023.
All research outputs
#16,051,682
of 25,387,189 outputs
Outputs from Optimization Letters
#58
of 523 outputs
Outputs of similar age
#210,425
of 417,113 outputs
Outputs of similar age from Optimization Letters
#2
of 36 outputs
Altmetric has tracked 25,387,189 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 523 research outputs from this source. They receive a mean Attention Score of 0.8. This one has done well, scoring higher than 87% 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 417,113 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.