We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa ...
Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L...
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
With more and more large networks becoming available, mining and querying such networks are increasingly important tasks which are not being supported by database models and query...