202 search results - page 5 / 41 » Privacy-preservation for gradient descent methods |
COLT
2010
Springer
13 years 3 months ago
2010
Springer
We present a new method for regularized convex optimization and analyze it under both online and stochastic optimization settings. In addition to unifying previously known firstor...
EOR
2000
13 years 5 months ago
2000
Training in the random neural network (RNN) is generally speci
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
JMLR
2012
11 years 7 months ago
2012
“Energy” models for continuous domains can be applied to many problems, but often suffer from high computational expense in training, due to the need to repeatedly minimize t...
IJIT
2004
13 years 6 months ago
2004
Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...