Learning Structured Outputs via Kernel Dependency Estimation and Stochastic Grammars
author:
Andrea Passerini,
Universita di Firenze
You might be experiencing some problems with Your Video player.
| Slides | |
| 0:02 | Learning Structured Outputs |
| 0:12 | The Idea in a Nutshell |
| 1:51 | Kernel Dependency Estimation |
| 2:51 | Output Feature Estimation Problem |
| 4:08 | Pre-image calculation |
| 5:18 | Using Stochastic Grammars |
| 5:55 | Using Stochastic Context Free Grammars |
| 8:00 | Experiments |
| 8:14 | Toy SCFG grammar |
| 9:56 | Data Preparation |
| 10:31 | Results (1) |
| 11:18 | Results (2) |
| 12:48 | Conclusions |
Lecture rating
| People found this lecture: | ||
| Worth seeing | ||
| because it is: | ||
| Valuable and informative | ||
| Well presented | ||
| Easily understandable | ||
| Acceptably recorded | ||
| You need to login to cast your vote. | ||
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Related content
Visitors who watched this lecture also watched...
SEE ALSO:
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !





