MIT News  March 30, 2023 While neural networks are used for classification tasks across domains, a long-standing open problem in machine learning is determining whether neural networks trained using standard procedures are consistent for classification, i.e., whether such models minimize the probability of misclassification for arbitrary data distributions. A team of researchers in the US (MIT, UC San Diego) identified, constructed and analyzed infinitely wide networks that were also infinitely deep. Using the recent connection between infinitely wide neural networks and neural tangent kernels, they provided explicit activation functions that could be used to construct networks that achieve consistency. They […]