Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
Data summarization is very important for many data analysis tasks. In this paper we propose a simple but efficient data summarization algorithm, which outputs a histogram for mult...
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...
With resource-efficient summarization and accurate reconstruction of the historic traffic sensor data, one can effectively manage and optimize transportation systems (e.g., road n...
Bei Pan, Ugur Demiryurek, Farnoush Banaei Kashani,...
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...