Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Motivated by applications like elections, web-page ranking, revenue maximization etc., we consider the question of inferring popular rankings using constrained data. More specific...
There has been increasing interest recently in meeting understanding, such as summarization, browsing, action item detection, and topic segmentation. However, there is very limite...
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...