The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
Frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. This paper takes a new approach for this problem and makes two major...
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
We address the problem of minimizing power consumption in behavioral synthesis of data-dominated circuits. The complex nature of power as a cost function implies that the effects ...
"This is a collection of algorithms for sorting and searching. Descriptions are brief and intuitive, with just enough theory thrown in to make you nervous. I assume you know C...