Section: Application Domains

Natural Language Processing

This year, our research has focused on new application domains within natural language processing (NLP), with our first two publications in leading conferences in NLP. We have worked on large-scale semantic role labelling (E. Grave, F. Bach, G. Obozinski), where we use syntactic dependency trees and learned representations from large corpora (e.g., 14.7 millions sentences, 310 millions tokens). We also extended our original work on structured sparsity to language models (F. Bach, A. Nelakanti, in collaboration with Xerox), in order to predict a word given all previous words, with a potentially infinite feature space organized with structured regularization.