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Double descent in human learning · Chris Said

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The uncanny resemblance between double descent and a 50 year old theory from psychology

Double descent in human learning · Chris Said --> Chris Said I am a data scientist at Propel. This blog is mostly about statistics, technology, and science. Double descent in human learning 21 Apr 2023 In machine learning, double descent is a surprising phenomenon where increasing the number of model parameters causes test performance to get better, then worse, and then better again. It refutes the classical overfitting finding that if you have too many parameters in your model, your test error will always keep getting worse with more parameters. For a surprisingly wide range of models

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