Computer Scientists Prove Why Bigger Neural Networks Do Better

Tuesday, February 15, 2022

A recent article in Quanta Magazine explored why neural networks must be much larger than conventionally expected. The findings, which come from a paper by Sébastien Bubeck of Microsoft Research and Mark Sellke of Stanford University, give some insight into a question that has come up repeatedly over several decades.

WNCG professor Alex Dimakis was quoted in the article, providing background on overparameterization in neural networks.

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