Concatenated Context Selected Linear Mapping for Neural Networks

 Learn the basics of CCSLM and neural networks from this video:



A key point is ReLU(W₁x) = DW₁x where D is a diagonal decision matrix with 0 or 1 entries according to the corresponding ReLU decisions. 

From the viewpoint of the weights in the next layer you have a binary context vector in the diagonal of D operating doing column suppression (parameter selection, linear mapping selection) W₂D but W₂D can be computed to a single matrix L=W₂D. 
All the data in the main data channel effectively sees is L and hence ReLU neural networks are concatenated context selected linear mappings.








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