This study examines the formation and change of collaborative learning social networks in a distributed learning community. A social network perspective is employed to understand how collaborative networks evolved over time when 31 distributed learners collaborated on a design project using a computer-mediated communication system during two semesters. Special attention was paid to how pre-exis...

A tensor network is a type of decomposition used to express and approximate large arrays data. given data-set, quantum state or higher dimensional multi-linear map factored approximated by composition smaller maps. This reminiscent how Boolean function might be decomposed into gate array: this represents special case decomposition, in which the entries are replaced 0, 1 factorisation becomes ex...

As the combination of parameter learning and structure learning, learning Bayesian networks can also be examined, Parameter learning is estimation of the dependencies in the network. Structural learning is the estimation of the links of the network. In terms of whether the structure of the network is known and whether the variables are all observable, there are four types of learning Bayesian n...