Title |
Universal gradient methods for convex optimization problems
|
---|---|
Published in |
Mathematical Programming, May 2014
|
DOI | 10.1007/s10107-014-0790-0 |
Authors |
Yu Nesterov |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 3% |
Germany | 1 | 1% |
Iran, Islamic Republic of | 1 | 1% |
New Zealand | 1 | 1% |
Russia | 1 | 1% |
Denmark | 1 | 1% |
Unknown | 80 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 33 | 38% |
Researcher | 11 | 13% |
Student > Doctoral Student | 10 | 11% |
Student > Master | 8 | 9% |
Professor | 6 | 7% |
Other | 13 | 15% |
Unknown | 7 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Mathematics | 28 | 32% |
Computer Science | 28 | 32% |
Engineering | 11 | 13% |
Business, Management and Accounting | 4 | 5% |
Decision Sciences | 3 | 3% |
Other | 4 | 5% |
Unknown | 10 | 11% |
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 10 May 2023.
All research outputs
#7,596,171
of 23,806,312 outputs
Outputs from Mathematical Programming
#139
of 697 outputs
Outputs of similar age
#71,579
of 228,199 outputs
Outputs of similar age from Mathematical Programming
#6
of 21 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 697 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 79% 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 228,199 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 67% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.