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Probabilistic bounds on best rank-1 approximation ratio

Overview of attention for article published in Linear and Multilinear Algebra, March 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

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Title
Probabilistic bounds on best rank-1 approximation ratio
Published in
Linear and Multilinear Algebra, March 2024
DOI 10.1080/03081087.2024.2304146
Authors

Khazhgali Kozhasov, Josué Tonelli-Cueto

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 September 2022.
All research outputs
#15,799,206
of 25,457,858 outputs
Outputs from Linear and Multilinear Algebra
#59
of 274 outputs
Outputs of similar age
#74,556
of 175,351 outputs
Outputs of similar age from Linear and Multilinear Algebra
#1
of 4 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 274 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done well, scoring higher than 78% 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 175,351 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 56% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them