Skip to content (access key 's')
Logo of Technion
Logo of CS Department
Events

Events

Theory Seminar: On Symmetry and Initialization for Neural Network
event speaker icon
Ido Nahum (Mathematics, Technion)
event date icon
Wednesday, 12.6.2019, 12:30
event location icon
Taub 201 Taub Bld.
This work provides an additional step in the theoretical understanding of neural networks. We consider neural networks with one hidden layer and show that when learning symmetric functions, one can choose initial conditions so that standard SGD training efficiently produces generalization guarantees. We empirically verify this and show that this does not hold when the initial conditions are chosen at random. The proof of convergence investigates the interaction between the two layers of the network. Our results highlight the importance of using symmetry in the design of neural networks.
[Back to the index of events]