Last month I became selected to develop a project for Shogun in the frame of GSoC. The project’s name is Build a Generic Structured Output Framework Learning and it is mentorized by Nico Görnitz. Here follows a short description of the project:
The aim is to implement tools for structured output (SO) problems. The data in these problems have complex structure (e.g. graphs, sequences) and the traditional learning algorithms fail to find solutions efficiently. Structured output support vector machines and conditional random fields are methods for SO learning. They will be implemented to form Shogun’s first module for SO learning. Finally, these methods will be applied to hidden Markov models-type of problems such as gene prediction.
Feel free to visit my project proposal where, among some personal information, you will be able to find a thorough description of the project together with a tentative schedule and useful references on the topic.
This is going to be a fun summer of coding!