Deep Learning for Machine Translation Winter School
First Call For Participation:
DL4MT Winter School
Deep Learning for Machine Translation
18-24 October 2015, Dublin City University, Dublin, Ireland
We would like to announce the Deep Learning For Machine Translation (DL4MT) Winter School at Dublin City University, Dublin, Ireland.
Over the last several years, Deep learning (DL) has been the driving force behind huge improvements in speech and image processing. This has led to high expectations for DL in NLP and MT. In recent top conferences, a significant portion of papers in the MT domain are related to DL. Some recent publications have shown the effectiveness of DL in various aspects of statistical MT. However, because of the complexity of the implementations and lack of enough details in some of these publications, it is difficult to repeat the work reported in these papers. Furthermore, we believe that many MT researchers currently lack the necessary expertise to incorporate DL into their research, despite having a high-level understanding of the uses of DL in the MT domain. Most major NLP conferences have included a deep-learning tutorial for the last 2-3 years. However, existing tutorials typically do not go into sufficient depth for participants to actually apply DL algorithms in their MT research. Because this field is evolving very quickly, we believe that a multi-day training event will help to prepare MT researchers to delve into DL, and give them the expertise to apply DL to their own work.
This one-week programme is sponsored by the European Association for Machine Translation (EAMT), and organised by The ADAPT Centre for Digital Content Technology..
We are pleased to announce three excellent mentors:
Prof. Kevin Duh, NAIST, Japan (will be affiliated with JHU, US during the winter school)
Prof. Hermann Ney, RWTH, Germany
Prof. Kyunghyun Cho, New York University, US
who will present talks on various aspects of DL, with a focus on applications to MT.
The core themes of the DL4MT workshop will cover:
The Fundamentals of DL4MT
Neural Language Models and Translation Models for SMT
Neural MT (Sequence to Sequence MT/Encoding-Decoding Models)
The structure of the DL4MT Winter School will be as follows: morning lectures will present in-depth interactive tutorials on topics in DL4MT, while afternoon sessions will be focused on implementation,
and will take place in a collaborative environment, with support from expert mentors.
We will solicit applications from MT researchers who have already used DL techniques in their work, and also from researchers who are interested in using DL, but would like to enhance their understanding of DL. This summer workshop focuses on applications of DL to MT, and attendees should leave with a deep understanding of the state-of-the-art in DL4MT, and the practical knowledge to implement the core algorithms in this area.
We will announce the application and registration process in the coming weeks.
Hope to see you in Dublin!