Ranking for inductive synthesis of string transformations
US9002758B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 17, 2012 |
| Grant date | Apr 7, 2015 |
| Priority date | — |
| Expiry date | Jul 8, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/151
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Ranking technique embodiments are presented that use statistical and machine learning techniques to learn the desired ranking function for use in inductive program synthesis for the domain of string transformations. This generally involves automatically creating a training dataset of positive and negative examples from a given set of training tasks, each including multiple input-output examples. From the training dataset, a ranking function is learned that assigns an expression in a program in the domain specific language to a likelihood measure. This ranking function is then used to compute likelihoods of learnt programs from a very small number of input-output examples for a new task.
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