Many existing techniques for term extraction are heuristically-motivated and criticised as ad-hoc. The definitions and assumptions critical to set the boundary for the effective...
Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as “learning objective”', “related concept”, etc. Manually ...
Paramjeet Singh Saini, Marco Ronchetti, Diego Sona
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Quantum systems are promising candidates of future computing and information processing devices. In a large system, information about the quantum states and processes may be incomp...