SF Big Analytics20171128: Google's Neural Machine Translation System and Research progress
Main Talk: Google's Neural Machine Translation System and Research progress
Abstract: Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems. In this talk, I will talk about the model architecture, word-pieces design, training algorithm and how to make training/serving faster. Possibly I will mention about the zero-shot for Multilingual model as well. Also, I will cover what/how translation research makes continuous progress from last year.
Speaker:Xiaobing Liu
Xiaobing Liu is Google Brain Staff software engineer and machine learning researcher. In his work, Xiaobing focuses on Tensorflow and some key applications where Tensorflow could be applied to improve Google products, such as Google Search, Play recommendation and Google translation and Medical Brain. His research interests span from system to the practice of machine learning. His research contributions have been successfully implemented into various commercial products at Tencent, Yahoo. and Google He has served in the program committee for ACL 2017 and session chair for AAAI 2017, including publications at top conference such as Recsys, NIPS, ACL.