This paper introduces deep syntactic structures to syntax-based Statistical Machine Translation (SMT). We use a Head-driven Phrase Structure Grammar (HPSG) parser to obtain the de...
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
Abstract: Information integration applications combine data from heterogeneous sources to assist the user in solving repetitive data-intensive tasks. Currently, such applications r...
Jim Blythe, Dipsy Kapoor, Craig A. Knoblock, Krist...
We describe an acoustic chord transcription system that uses symbolic data to train hidden Markov models and gives best-of-class frame-level recognition results. We avoid the extre...
Most highly accurate predictive modeling techniques produce opaque models. When comprehensible models are required, rule extraction is sometimes used to generate a transparent mod...