311 search results - page 2 / 63 » Gradient Convergence in Gradient methods with Errors |
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
The method of conjugate gradients provides a very effective way to optimize large, deterministic systems by gradient descent. In its standard form, however, it is not amenable to ...
AMC
2008
13 years 5 months ago
2008
Abstract: The nonlinear conjugate gradient method is widely used in unconstrained optimization. However, the line search is very difficult or expensive sometimes. In this paper, we...
ALT
2004
Springer
14 years 2 months ago
2004
Springer
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
CORR
2011
Springer
13 years 10 days ago
2011
Springer
Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...