Convolutional Competitive Learning vs. Sparse Autoencoders (2/2)
This is the second part of our comparison between convolutional competitive learning and convolutional or fully-connected sparse autoencoders. To understand our motivation for this comparison, have a look at the first article. We decided to compare two specific algorithms that tick most of the features we require: K-Sparse autoencoders, and Growing-Neural-Gas-with-Utility (GNG-U) (Fritzke1997). The latter…

