Daniel Beck

Learning Structural Kernels for Natural Language Processing

2015 · White Rose Research Online (University of Leeds, The University of Sheffield, University of York)

Structural kernels are a flexible learning paradigm that has been widely used in Natural Language Processing. However, the problem of model selection in kernel-based methods is usually overlooked. Previous approaches mostly rely on setting default …

Graph-to-Sequence Learning using Gated Graph Neural Networks

2018

Many NLP applications can be framed as a graph-to-sequence learning problem. Previous work proposing neural architectures on this setting obtained promising results compared to grammar-based approaches but still rely on linearisation heuristics and/or standard recurrent …