XML data integration tools are facing a variety of challenges for their efficient and effective operation. Among these is the requirement to handle a variety of inconsistencies or...
Sudipto Guha, Nick Koudas, Divesh Srivastava, Ting...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Identifying a minimal unsatisfiable core in an Alloy model proved to be a very useful feature in many scenarios. We extend this concept to hot core, an approximation to unsat core...