Events Calendar

CS Colloquium: Kyunghyun Cho (NYU) - Neural machine translation - Progress Report

Speaker: Kyunghyun Cho, NYU

Talk Title: Neural machine translation -- Progress Report

Series: CS Colloquium

Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium

Neural machine translation is a recently proposed framework for machine translation, which is purely based on neural networks. Neural machine translation radically departs from the existing, widely-used, often phrase-based statistical machine translation by viewing the task of machine translation as a supervised, structured output prediction problem and solving it with recurrent neural networks. In this talk, I will describe in detail what neural machine translation is and discuss recent advances which have made it possible for neural machine translation system to be competitive with the conventional statistical approach. I will conclude the talk by presenting my view on the future of machine translation and a big question of "is natural language special?"

The lecture will be available to stream HERE.

Biography: Kyunghyun Cho is an assistant professor of Computer Science and Data Science at New York University (NYU). Previously, he was a postdoctoral researcher at the University of Montreal under the supervision of Prof. Yoshua Bengio after obtaining a doctorate degree at Aalto University (Finland) in early 2014. Kyunghyun's main research interests include neural networks, generative models and their applications, especially, to language understanding.

Host: Yan Liu

Webcast: https://bluejeans.com/506861099

Location: Henry Salvatori Computer Science Center (SAL) - 101

WebCast Link: https://bluejeans.com/506861099

Audiences: Everyone Is Invited

Contact: Assistant to CS chair