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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Towards a Learning-Based Performance Modeling for Accelerating Deep Neural Networks
|
|---|---|
| Chapter number | 49 |
| Book title |
Computational Science and Its Applications – ICCSA 2019
|
| Published in |
arXiv, July 2019
|
| DOI | 10.1007/978-3-030-24289-3_49 |
| Book ISBNs |
978-3-03-024288-6, 978-3-03-024289-3
|
| Authors |
Damiano Perri, Paolo Sylos Labini, Osvaldo Gervasi, Sergio Tasso, Flavio Vella, Perri, Damiano, Sylos Labini, Paolo, Gervasi, Osvaldo, Tasso, Sergio, Vella, Flavio |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 1 | 100% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 1 | 100% |
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 12 December 2022.
All research outputs
#19,594,120
of 24,093,053 outputs
Outputs from arXiv
#580,062
of 1,018,817 outputs
Outputs of similar age
#264,254
of 352,249 outputs
Outputs of similar age from arXiv
#16,148
of 28,636 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,018,817 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 26th percentile – i.e., 26% 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 352,249 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28,636 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.