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Added by Vincent Granville on August 30, 2020 at 12:30pm — No Comments
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Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…
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Given n observations x1, ..., xn, the generalized mean (also called power mean) is defined as
The case p = 1 corresponds to the traditional arithmetic mean, while p = 0 yields the geometric mean, and p = -1…
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Originally posted here.
Added by Vincent Granville on August 20, 2020 at 1:09pm — No Comments
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Added by Vincent Granville on August 20, 2020 at 9:00am — No Comments
It took me about 30 minutes to notice a spectacular correlation between two core metrics related to the virus, allowing me to make better predictions about the evolution of this pandemic in USA, and to provide possibly the best advice on how to reduce your risk of exposure, or at least how to buy some time in the war against this virus.
First, many metrics are useless, you need to pick up the most reliable ones. For instance, the number of people who officially tested positive is…
ContinueAdded by Vincent Granville on August 18, 2020 at 10:30am — 9 Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…
ContinueAdded by Vincent Granville on August 16, 2020 at 4:30pm — No Comments
Here is our selection of featured technical resources and articles posted since Monday:
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ContinueAdded by Vincent Granville on August 13, 2020 at 12:00pm — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.
Featured Resources and…
Added by Vincent Granville on August 9, 2020 at 2:30pm — No Comments
The covariance matrix has many interesting properties, and it can be found in mixture models, component analysis, Kalman filters, and more. Developing an intuition for how the covariance matrix operates is useful in understanding its practical implications. This article will focus on a few important properties, associated proofs, and then some interesting practical applications, i.e., extracting transformed polygons from a Gaussian mixture's covariance matrix.
I have often found that…
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Added by Vincent Granville on August 6, 2020 at 11:30am — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.
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