Musings on Deep Learning: Properties of SGD

TitleMusings on Deep Learning: Properties of SGD
Publication TypeCBMM Memos
Year of Publication2017
AuthorsZhang, C, Liao, Q, Rakhlin, A, Sridharan, K, Miranda, B, Golowich, N, Poggio, T
Date Published04/2017

[formerly titled "Theory of Deep Learning III: Generalization Properties of SGD"]

In Theory III we characterize with a mix of theory and experiments the generalization properties of Stochastic Gradient Descent in overparametrized deep convolutional networks. We show that Stochastic Gradient Descent (SGD) selects with high probability solutions that 1) have zero (or small) empirical error, 2) are degenerate as shown in Theory II and 3) have maximum generalization.


CBMM Memo No:  067

Research Area: 

CBMM Relationship: 

  • CBMM Funded