Invited Speaker | |
 | Fernando PereiraVP and Engineering Fellow at Google |
Representation learning, inference, and reasoning
Abstract
Advances in deep learning have led to a golden age of increasingly rich models of language with large experimental gains in practical language understanding tasks. However, these gains came at the expense of structured inference for global constraint satisfaction and multistep reasoning. I will illustrate this with examples that are obvious for people but pose unsolved inference and reasoning challenges to current ML methods. I will conclude with questions and proposed tasks that may sharpen our understanding of these issues.