About
Dzmitry Bahdanau’s research goal is to further the adoption and widespread use of language user interfaces for human-computer interaction. His research seeks to align ideas from the disciplines of deep learning, linguistic and symbolic AI. Topics of key interest to Dzmitry include semantic parsing and task-oriented dialogue models, in particular making such models generalize more systematically, perform effectively with less training data and be easily adaptable to new domains.
Relevant Publications
- Bahdanau, D., Murty, S., Noukhovitch, M., Nguyen, T. H., de Vries, H., & Courville, A. (2018). Systematic generalization: what is required and can it be learned?. arXiv preprint arXiv:1811.12889.
- Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.
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