Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
We explore the phenomena of subjective randomness as a case study in understanding how people discover structure embedded in noise. We present a rational account of randomness per...
Annotation Enrichment Analysis (AEA) is a widely used analytical approach to process data generated by high-throughput genomic and proteomic experiments such as gene expression mic...