MLT "Women in Machine Learning" in collaboration with Google Japan is part of our Diversity and Inclusion efforts.
This event aims to inform, support and empower women considering a career in Machine Learning (engineering and research), Data Science and related fields.
This is an inclusive event, we welcome all people to join, regardless of gender or background.
In this first NLP paper reading session we will discuss the paper
"A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning", which won the test-of-time award in the 2018 International Conference of Machine Learning.
This paper was written by Ronan Collobert and Jason Weston, and published in 2008 in the same conference.
We will talk about concepts ranging from word embeddings to training auxiliary tasks as means to improve modeling power, and understand why some of the concepts presented ten years ago are still widely-used today.