See my website for more information: Website
Miguel Ballesteros is a postdoc at Universitat Pompeu Fabra.
Miguel's main research interest relies on applying new methods for automatic feature selection in order to speed up and facilitate the process of optimizing a data-driven dependency parser. Besides this, he is carrying out several experiments by modifying the work-flow and behaviour of current transition-based and graph-based dependency parsing algorithms with the intention of enhancing the performance and speeding up the training process.
- April 2012. Release of MaltOptimizer: Miguel and Joakim Nivre have released MaltOptimizer, a tool for MaltParser optimization and automatic feature selection. They demonstrated the system at EACL 2012 and Miguel presented it at LREC 2012.
- Dependency Parsing.
- Data-Driven Dependency Parsing.
- Machine Learning for Natural Language Processing.
- Algorithms for natural language processing.
- Processing negation and modality.
- Simplified Texts.
- Design principles and annotation schemes for treebanks.