Machine learning & AI
According to collective intelligence evangelist and journalist James Surowiecki, groups are much better at making predictions than the individuals who belong to those groups, be they novices or leading experts.
Dec 23, 2021
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20
Consumer & Gadgets
Users typically react to social media outages with angry tirades and barbed jokes. But researchers suggest that this lack of social media access offers a glimpse into the importance of social media not just as a tool to socialize ...
May 4, 2022
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61
Energy & Green Tech
What do a T-shirt, a rug, and a soda bottle have in common? Many are made from polyethylene terephthalate (PET), a ubiquitous plastic that revolutionized the materials industry after it was patented in the 1940s.
Dec 22, 2022
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60
Computer Sciences
A new study by the Oregon State University College of Engineering shows that machine learning techniques can offer powerful new tools for advancing personalized medicine, care that optimizes outcomes for individual patients ...
Dec 9, 2021
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380
Machine learning & AI
Roses are red violets are blue, AI writing poems? Can't be true. Or can it? And if so, how low can we go in expectations? Brush low expectations aside for now, as Google is on to something special, and that is, AI for self-portrait ...
May 4, 2019 weblog
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63
Computer Sciences
A new study by MIT researchers finds that the growing practice of compiling massive, anonymized datasets about people's movement patterns is a double-edged sword: While it can provide deep insights into human behavior for ...
Dec 7, 2018
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34
Computer Sciences
Over the past 20 years, the number of passengers traveling on British train networks has almost doubled to 1.7 billion annually. With numbers like that it's clear how much people rely on rail service in Great Britain, and ...
Dec 11, 2020
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69
Energy & Green Tech
In the future, the energy needed to run the powerful computers on board a global fleet of autonomous vehicles could generate as many greenhouse gas emissions as all the data centers in the world today.
Jan 12, 2023
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72
Computer Sciences
A child who has never seen a pink elephant can still describe one—unlike a computer. "The computer learns from data," says Jiajun Wu, a Ph.D. student at MIT. "The ability to generalize and recognize something you've never ...
Apr 3, 2019
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38
Energy & Green Tech
A new mathematical model for predicting variations in solar irradiance has been developed at Uppsala University. It may help to promote more efficient use of electricity from solar energy. In tests of various data models, ...
Jun 29, 2020
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47
A statistical model is a set of mathematical equations which describe the behavior of an object of study in terms of random variables and their associated probability distributions. If the model has only one equation it is called a single-equation model, whereas if it has more than one equation, it is known as a multiple-equation model.
In mathematical terms, a statistical model is frequently thought of as a pair (Y,P) where Y is the set of possible observations and P the set of possible probability distributions on Y. It is assumed that there is a distinct element of P which generates the observed data. Statistical inference enables us to make statements about which element(s) of this set are likely to be the true one.
Three notions are sufficient to describe all statistical models.
One of the most basic models is the simple linear regression model which assumes a relationship between two random variables Y and X. For instance, one may want to linearly explain child mortality in a given country by its GDP. This is a statistical model because the relationship need not to be perfect and the model includes a disturbance term which accounts for other effects on child mortality other than GDP.
As a second example, Bayes theorem in its raw form may be intractable, but assuming a general model H allows it to become
which may be easier. Models can also be compared using measures such as Bayes factors or mean square error.
This text uses material from Wikipedia, licensed under CC BY-SA
