Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
—Flow correlation algorithms compare flows to determine similarity, and are especially useful and well studied for detecting flow chains through “stepping stone” hosts. Most ...
W. Timothy Strayer, Christine E. Jones, Beverly Sc...
We discover significant value-dependent programming energy variations in multi-level cell (MLC) flash memories, and introduce an energy-aware data compression method that minimize...