##### Thesis seminar - The Sparse Manifold Transform and Unsupervised Learning for Signal Representation

###### Yubei Chen

###### EECS, UC Berkeley

In this talk, I will first present a signal representation framework called the Sparse Manifold Transform that combines key ideas from sparse coding, manifold learning, and slow feature analysis. It turns non-linear transformations in the primary sensory signal space into linear interpolations in a representational embedding space while maintaining approximate invertibility. The sparse manifold transform is an