54 search results - page 6 / 11 » A sparse variational Bayesian approach for fMRI data analysi... |
ICMLA
2008
13 years 9 months ago
2008
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
BMCBI
2010
13 years 7 months ago
2010
Background: Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variat...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
Nuclear magnetic resonance (NMR) spectral analysis has recently become one of the major means for the detection and recognition of metabolic changes of disease state, physiologica...
PR
2011
13 years 2 months ago
2011
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
PERCOM
2007
ACM
14 years 7 months ago
2007
ACM
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...