Machine Translation with Recurrent Neural Networks
- Status
- Open
- Type
- Master Thesis
- Announcement date
- 06 Oct 2015
- Mentors
- Research Areas
Short Description
neural translation models
Your Tasks
- Redroduce and compare to state-of-the-art neural translation models
- Extend existing models in Python and Theano (libary for GPU computing)
- Analyze the implemented systems in terms of accuracy and computational performance
Your Profile
- Very good theoretical and mathmatical background (mandatory)
- Good knowledge in machine learning
- Very good knowledge and experience in Python programming (mandatory)
Additional Information
As this work combines theoretical and experimental aspects of non-standard methods, a very good mathmatical and programming background is mandatory. This thesis project is planned for a duration of 6 months starting immediately. It has a good chance for publications.
Contact
Martin Ratajczak (martin.ratajczak@tugraz.at or +43 (316) 873 - 4379)
References
[1] D. Bahdanau, K. Cho, andY. Bengio. Neuralmachine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473, 2014
[2] I. Sutskever, O. Vinyals, Q. V. Le. Sequence to Sequence Learning with Neural Networks, 2014