Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones?

14 May 2020Nadezhda ChirkovaEkaterina LobachevaDmitry Vetrov

One of the generally accepted views of modern deep learning is that increasing the number of parameters usually leads to better quality. The two easiest ways to increase the number of parameters is to increase the size of the network, e.g. width, or to train a deep ensemble; both approaches improve the performance in practice... (read more)

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