Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

February 1, 2005, Vol. 17, No. 2, Pages 487-502
(doi: 10.1162/0899766053011519)
© 2005 Massachusetts Institute of Technology
Loading Deep Networks Is Hard: The Pyramidal Case
Article PDF (123.1 KB)
Abstract

The question of whether it is possible to load deep neural network architectures efficiently is examined by considering the class of pyramidal architectures. This class allows only a low interaction of the nodes. Still, the loading problem is found to be NP-complete. This provides evidence that depth alone is a factor accounting for loading hardness.