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TD-regularized actor-critic methods

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

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

twitter
10 X users

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
68 Mendeley
Title
TD-regularized actor-critic methods
Published in
Machine Learning, February 2019
DOI 10.1007/s10994-019-05788-0
Authors

Simone Parisi, Voot Tangkaratt, Jan Peters, Mohammad Emtiyaz Khan

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 25%
Student > Master 11 16%
Researcher 7 10%
Student > Doctoral Student 6 9%
Student > Bachelor 4 6%
Other 6 9%
Unknown 17 25%
Readers by discipline Count As %
Computer Science 21 31%
Engineering 14 21%
Neuroscience 3 4%
Economics, Econometrics and Finance 2 3%
Mathematics 2 3%
Other 5 7%
Unknown 21 31%
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 03 April 2019.
All research outputs
#8,087,915
of 24,980,180 outputs
Outputs from Machine Learning
#298
of 1,149 outputs
Outputs of similar age
#141,948
of 359,219 outputs
Outputs of similar age from Machine Learning
#2
of 12 outputs
Altmetric has tracked 24,980,180 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 1,149 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 73% 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 359,219 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 59% of its contemporaries.
We're also able to compare this research output to 12 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 91% of its contemporaries.