Uri Shaham - Deep Learning for Representation Learning
In this talk I will present two deep learning-based algorithms for representation learning.
In the first half of the talk I will present SpectralNet, a deep learning approach for spectral clustering, which is scalable and allows for straight-forward out of sample extension.
In the second half of the talk I will present a deep learning approach for recovery of a single independent component of interest, given another component as a condition.