Learning a good representation is a crucial step in many machine learning pipelines. One common technique to do so is to use Stacked Denoising Autoencoders (SDAEs). In this talk I will go over the basics of Stacked Denoising Autoencoders. We will that are superior to many forms of pre-training. I will then present how Random Matrix Theory can be used to understand their superior performance. Speaker(s): Rishi Sonthalia (University of Michigan)