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If you have a question about this talk, please contact nobody. MDL - Mathematics of deep learning I will present the paper “A mean field limit for certain deep neural networks” by DYEGO ARA ÚJO, ROBERTO I . OLIVEIRA & DANIEL YUKIMURA . I recent years, increased attention has been paid to DNNs with high numbers of parameters, after observations that the classical bias-variance tradeoff principle fails to paint an accurate picture of the behaviour of NNs as the dimension of their parameter space tends to infinity. This motivated several lines of reasearch into the limiting behaviour of NNs under various scaling frameworks. The paper above presents a self contained and intuitive description of this phenomenon. I’ll try to shine some light under the complex notation and to explain the major ideas behind the results. This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
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