Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
We study the problem of visualizing large networks and develop es for effectively abstracting a network and reducing the size to a level that can be clearly viewed. Our size reduc...
Discovery of association rules is a prototypical problem in data mining. The current algorithms proposed for data mining of association rules make repeated passes over the databas...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, We...
We study a variant of the classical circuit-lower-bound problems: proving lower bounds for sampling distributions given random bits. We prove a lower bound of 1 - 1/n(1) on the st...
Abstract. Pearson product-moment correlation coefficients are a wellpracticed quantification of linear dependence seen across many fields. When calculating a sample-based correlati...
Taylor Phillips, Chris GauthierDickey, Ramki Thuri...