The present work studies clustering from an abstract point of view and investigates its properties in the framework of inductive inference. Any class S considered is given by a hyp...
John Case, Sanjay Jain, Eric Martin, Arun Sharma, ...
The highly variable and dynamic word usage in social media presents serious challenges for both research and those commercial applications that are geared towards blogs or other u...
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...
This paper provides an overview of the foundations of the run-time semantics underlying the Unified Modeling Language as defined in revision 2.0 of the official OMG standard. One o...
A strong inductive bias is essential in unsupervised grammar induction. In this paper, we explore a particular sparsity bias in dependency grammars that encourages a small number ...