| Title |
Linear Programming Boosting via Column Generation
|
|---|---|
| Published in |
Machine Learning, January 2002
|
| DOI | 10.1023/a:1012470815092 |
| Authors |
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Taylor |
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 % |
|---|---|---|
| Japan | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 4% |
| Japan | 2 | 1% |
| Turkey | 1 | <1% |
| France | 1 | <1% |
| Italy | 1 | <1% |
| Netherlands | 1 | <1% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Other | 5 | 3% |
| Unknown | 137 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 60 | 38% |
| Student > Master | 21 | 13% |
| Researcher | 20 | 13% |
| Professor > Associate Professor | 10 | 6% |
| Professor | 10 | 6% |
| Other | 27 | 17% |
| Unknown | 9 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 87 | 55% |
| Engineering | 23 | 15% |
| Mathematics | 7 | 4% |
| Agricultural and Biological Sciences | 5 | 3% |
| Biochemistry, Genetics and Molecular Biology | 4 | 3% |
| Other | 13 | 8% |
| Unknown | 18 | 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 31 December 2022.
All research outputs
#7,356,343
of 25,374,647 outputs
Outputs from Machine Learning
#269
of 1,225 outputs
Outputs of similar age
#26,104
of 130,780 outputs
Outputs of similar age from Machine Learning
#3
of 8 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,225 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done well, scoring higher than 76% 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 130,780 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
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.