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Current and future algorithms in machine-learning

5 years 3 months ago #751 by Dorina Grossu
"The goal of learning a predictor (a mathematical function that can be used to make predictions) from a database of random examples was formalized in the aptly named probably approximately correct (PAC) learning model. In this model, the aim is to train the predictor to match some true function that labels the data. A different model, called online learning, has the learner making immediate predictions as data arrive — for example, capturing a trading system’s task of executing transactions in an ever-changing market. And another model known as multi-armed bandits can simulate clinical trials, in which the medical outcomes that an experimenter observes depend on his or her own choices."
"Machine learning has matured as a mathematical discipline and now joins the many subfields of mathematics that deal with the burden of unprovability and the unease that comes with it. Perhaps results such as this one will bring to the field of machine learning a healthy dose of humility, even as machine-learning algorithms continue to revolutionize the world around us."

Guess where do we go? Each living being is unique therefore it deserves the same respect.

https://www.nature.com/articles/d41586-019-00012-4

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