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Sample size selection in optimization methods for machine learning

Overview of attention for article published in Mathematical Programming, June 2012
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

patent
3 patents

Citations

dimensions_citation
235 Dimensions

Readers on

mendeley
187 Mendeley
citeulike
1 CiteULike
Title
Sample size selection in optimization methods for machine learning
Published in
Mathematical Programming, June 2012
DOI 10.1007/s10107-012-0572-5
Authors

Richard H. Byrd, Gillian M. Chin, Jorge Nocedal, Yuchen Wu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Japan 2 1%
Australia 1 <1%
United Kingdom 1 <1%
Korea, Republic of 1 <1%
Switzerland 1 <1%
Canada 1 <1%
Spain 1 <1%
Unknown 176 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 56 30%
Researcher 34 18%
Student > Master 17 9%
Student > Postgraduate 9 5%
Student > Doctoral Student 8 4%
Other 24 13%
Unknown 39 21%
Readers by discipline Count As %
Computer Science 54 29%
Engineering 26 14%
Mathematics 21 11%
Agricultural and Biological Sciences 5 3%
Biochemistry, Genetics and Molecular Biology 4 2%
Other 31 17%
Unknown 46 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 July 2022.
All research outputs
#7,468,426
of 22,831,537 outputs
Outputs from Mathematical Programming
#145
of 677 outputs
Outputs of similar age
#54,822
of 164,634 outputs
Outputs of similar age from Mathematical Programming
#1
of 5 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 677 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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 164,634 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them