What can you do about data sparsity? What do you do when you have a matrix with a bunch of zeros in it, and you can't get a good look at a complex system because so many of the nodes are empty? Matrix ...

Detection methods based on deep convolutional networks search for interest points by constructing response maps using supervised, self-supervised, and unsupervised methods. Supervised methods use ...

Sparsity is a measured way of optimizing machine learning models by deliberately specifying which nodes are composed of zero values. Sparse models, as opposed to dense models, contain mostly zero ...