Rich prior knowledge in learning for natural language processing
, Researcher,Institute for Systems and Computer Engineering (INESC), Lisbon, Portugal.
We possess a wealth of prior knowledge about most prediction problems, and particularly so for many of the fundamental tasks in natural language processing. Unfortunately, it is often difficult to make use of this type of information during learning, as it typically does not come in the form of labeled examples, may be difficult to encode as a prior on parameters in a Bayesian setting, and...
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Published on : Friday 24 October 2014