Learning efficiently with approximate inference via dual losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation. Previous approaches for learning for structured prediction (e.g., cutting- plane, subgradient methods, perceptron)...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
International Machine Learning Society
2011
|
| Online Access: | http://hdl.handle.net/1721.1/62851 https://orcid.org/0000-0002-2199-0379 |