The desirable asymptotic optimality properties of the maximum likelihood (ML) estimator make it an attractive solution for performing independent component analysis (ICA) as well....
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Conventional Difference of Gaussian (DOG) filter is usually used to model the early stage of visual processing. However, convolution operation used with DOG does not explicitly a...