Technique to make NN (specifically autoencoders) more robust by artifcally making input data more sparse
I've finally found it. The term I was looking for was 'masking corruption' and is mentioned in 'Practical Recommendations for Gradient-Based Training of Deep Architectures' by Yoshua Bengio.