| Title |
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review
|
|---|---|
| Published in |
Machine Intelligence Research, March 2017
|
| DOI | 10.1007/s11633-017-1054-2 |
| Authors |
Tomaso Poggio, Hrushikesh Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao |
X Demographics
The data shown below were collected from the profiles of 4 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 | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 754 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | <1% |
| Canada | 2 | <1% |
| Switzerland | 1 | <1% |
| Finland | 1 | <1% |
| New Zealand | 1 | <1% |
| Germany | 1 | <1% |
| China | 1 | <1% |
| Singapore | 1 | <1% |
| Unknown | 739 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 180 | 24% |
| Researcher | 119 | 16% |
| Student > Master | 113 | 15% |
| Student > Bachelor | 65 | 9% |
| Other | 33 | 4% |
| Other | 113 | 15% |
| Unknown | 131 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 243 | 32% |
| Engineering | 128 | 17% |
| Mathematics | 51 | 7% |
| Physics and Astronomy | 38 | 5% |
| Neuroscience | 23 | 3% |
| Other | 104 | 14% |
| Unknown | 167 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 63. 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 13 August 2022.
All research outputs
#688,632
of 26,017,215 outputs
Outputs from Machine Intelligence Research
#1
of 465 outputs
Outputs of similar age
#14,219
of 325,998 outputs
Outputs of similar age from Machine Intelligence Research
#1
of 13 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 465 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 99% 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 325,998 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 13 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 92% of its contemporaries.