2 search results - page 1 / 1 » Scalable training of L1-regularized log-linear models |
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
NIPS
2007
13 years 6 months ago
2007
We demonstrate that log-linear grammars with latent variables can be practically trained using discriminative methods. Central to efficient discriminative training is a hierarchi...