The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
Dynamic functional imaging promises powerful tools for the visualization and elucidation of important diseasecausing biological processes, where the pixels often represent a compo...
Li Chen, Tsung-Han Chan, Peter L. Choyke, Chong-Yu...
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
This paper advocates that cache coherence protocols use a bandwidth adaptive approach to adjust to varied system configurations (e.g., number of processors) and workload behaviors...
Milo M. K. Martin, Daniel J. Sorin, Mark D. Hill, ...
This paper proposes a generic framework for monitoring continuous spatial queries over moving objects. The framework distinguishes itself from existing work by being the first to ...