@inproceedings{87e7a99f67ad4f5387813dbcbe17b3be,

title = "Improving generalization performance in character recognition",

abstract = "One test of a new training algorithm is how well the algorithm generalizes from the training data to the test data. A new training algorithm termed double backpropagation improves generalization by minimizing the change in the output due to small changes in the input. This is accomplished by minimizing the normal energy term found in backpropagation and an additional energy term that is a function of the Jacobian.",

author = "Harris Drucker and Cun, {Yann Le}",

year = "1991",

language = "English (US)",

isbn = "0780301188",

series = "Neural Networks for Signal Processing",

publisher = "Publ by IEEE",

pages = "198--207",

booktitle = "Neural Networks for Signal Processing",

note = "Proceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91 ; Conference date: 30-09-1991 Through 02-10-1991",

}