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Data scarcity, robustness and extreme multi-label classification

Overview of attention for article published in Machine Learning, March 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
67 Dimensions

Readers on

mendeley
79 Mendeley
Title
Data scarcity, robustness and extreme multi-label classification
Published in
Machine Learning, March 2019
DOI 10.1007/s10994-019-05791-5
Authors

Rohit Babbar, Bernhard Schölkopf

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 20%
Student > Master 10 13%
Student > Bachelor 8 10%
Researcher 6 8%
Student > Doctoral Student 3 4%
Other 8 10%
Unknown 28 35%
Readers by discipline Count As %
Computer Science 26 33%
Engineering 9 11%
Physics and Astronomy 2 3%
Business, Management and Accounting 2 3%
Agricultural and Biological Sciences 1 1%
Other 6 8%
Unknown 33 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 September 2020.
All research outputs
#15,572,469
of 23,146,350 outputs
Outputs from Machine Learning
#664
of 981 outputs
Outputs of similar age
#237,575
of 380,346 outputs
Outputs of similar age from Machine Learning
#3
of 8 outputs
Altmetric has tracked 23,146,350 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 981 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 21st percentile – i.e., 21% 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 380,346 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 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.