12 - 14 June 2017, Conference on Logic and Machine Learning in Natural Languages (LaML), Goeteborg, Sweden
The past two decades have seen impressive progress in a variety of areas of AI, particularly NLP, through the application of machine learning methods to a wide range of tasks. While deep learning is opening up exciting new approaches to longstanding, difficult problems in computational linguistics, it also raises important foundational questions. Specifically, we do not have a clear formal understanding of why multi-level recursive deep neural networks achieve the success in learning and classification that they are delivering. It is also not obvious whether they should displace more traditional, logically driven methods, or be combined with them. Finally, we need to explore the extent, if any, to which both logical models and machine learning methods offer insights into the cognitive foundations of natural language.
The Conference on Logic and Machine Learning in Natural Language will address these questions and related issues. It will feature invited talks by leading researchers in both fields, and high level contributed papers selected through open competition and rigorous review. Our aim is to initiated a genuine dialogue between these two approaches, where they have traditionally remained separate and in competition.
We anticipate accepting 17 papers for oral presentation, and up to 20 papers for poster presentation.