TY - JOUR
T1 - Back-propagation is significantly faster if the expected value of the source unit is used for update
AU - Samad, Tariq
PY - 1988
Y1 - 1988
N2 - It has frequently been remarked that a major drawback of the back-propagation learning rule, and one that does not bode well for its application to real-world problems, is its poor scaling properties - with large networks, back-propagation can take infeasibly long to converge. The research outlined shows that an intuitively straightforward modification of back-propagation can greatly improve its performance, particularly for large and structured networks.
AB - It has frequently been remarked that a major drawback of the back-propagation learning rule, and one that does not bode well for its application to real-world problems, is its poor scaling properties - with large networks, back-propagation can take infeasibly long to converge. The research outlined shows that an intuitively straightforward modification of back-propagation can greatly improve its performance, particularly for large and structured networks.
UR - http://www.scopus.com/inward/record.url?scp=0024167370&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0024167370&partnerID=8YFLogxK
U2 - 10.1016/0893-6080(88)90253-5
DO - 10.1016/0893-6080(88)90253-5
M3 - Conference article
AN - SCOPUS:0024167370
SN - 0893-6080
VL - 1
SP - 216
JO - Neural Networks
JF - Neural Networks
IS - 1 SUPPL
T2 - International Neural Network Society 1988 First Annual Meeting
Y2 - 6 September 1988 through 10 September 1988
ER -