2 search results - page 1 / 1 » Scalable training of L1-regularized log-linear models |
90
Voted
ICML
2007
IEEE
16 years 1 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...
104
Voted
NIPS
2007
15 years 2 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...