Invited Talk 6 - Nathan Srebro

Geometry, Optimization and Generalization in Multilayer Networks

What is it that enables learning with multi-layer networks? What causes the network to generalize well despite the model class having extremely high capacity? In this talk I will explore these questions through experimentation, analogy to matrix factorization (including some new results on the energy landscape and implicit regularization in matrix factorization), and study of alternate geometries and optimization approaches.