58 search results - page 5 / 12 » Using Gradient Descent Optimization for Acoustics Training f... |
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
TNN
2010
13 years 2 months ago
2010
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
SDM
2011
SIAM
12 years 10 months ago
2011
SIAM
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
JMLR
2008
13 years 7 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...