CMPSC 291K Deep Learning for Machine Translation

This course will cover deep learning methods for neural machine translation and text generation. It will cover neural models for discrete sequences including Long-short term memory, Transformer, and encoder-decoder frameworks for generating language. It includes training objectives and optimization algorithms for learning those models. It will also include strategy such as back-translation, knowledge distillation. Finally, it will cover multilingual machine translation, low-resource translation, speech translation, and visual translation.

Prerequisites: 130A or 130B; 165A or 165B.

Text (optional): Neural Machine Translation, Philipp Koehn, ISBN-10: 1108497322, Publisher: Cambridge University Press