Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
We study query authentication schemes, algorithmic and cryptographic constructions that provide efficient and secure protocols for verifying the results of queries over structured...
Performance prediction has gained increasing attention in the IR field since the half of the past decade and has become an established research topic in the field. The present work...
Transformation of a source schema with its conforming data to a target schema with its conforming data is an important activity in XML as two schemas in XML can represent same rea...