Paper: Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions

ACL ID N10-1112
Title Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

We describe a method of incorporating task- specific cost functions into standard condi- tional log-likelihood (CLL) training of linear structured prediction models. Recently intro- duced in the speech recognition community, we describe the method generally for struc- tured models, highlight connections to CLL and max-margin learning for structured pre- diction (Taskar et al., 2003), and show that the method optimizes a bound on risk. The approach is simple, efficient, and easy to im- plement, requiring very little change to an existing CLL implementation. We present experimental results comparing with several commonly-used methods for training struc- tured predictors for named-entity recognition.