Linear models have enjoyed great success in structured prediction in NLP. While a lot of progress has been made on efficient training with several loss functions, the problem of ...
Statistical bilingual word alignment has been well studied in the context of machine translation. This paper adapts the bilingual word alignment algorithm to monolingual scenario ...
We present new training methods that aim to mitigate local optima and slow convergence in unsupervised training by using additional imperfect objectives. In its simplest form, lat...
Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jura...
One way to address the continuing performance problem of high-level domain-specific languages, such as Octave or MATLAB, is to compile them to a relatively lower level language f...
Abstract The Haskell String type is notoriously inefficient. We introduce a new data type, ByteString, based on lazy lists of byte arrays, combining the speed benefits of strict a...