We propose a corpus-based probabilistic framework to extract hidden common syntax across languages from non-parallel multilingual corpora in an unsupervised fashion. For this purp...
We present a general-purpose, lossless compressor for streaming data. This compressor is based on the deplump probabilistic compressor for batch data. Approximations to the infere...
With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
We propose a multivariate decision tree inference scheme by using the minimum message length (MML) principle (Wallace and Boulton, 1968; Wallace and Dowe, 1999). The scheme uses MM...
The paper introduces a generalization for known probabilistic models such as log-linear and graphical models, called here multiplicative models. These models, that express probabi...