A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
—We document methods for the quantitative evaluation of systems that produce a scalar summary of a biometric sample’s quality. We are motivated by a need to test claims that qu...
Hierarchical HMM (HHMM) parsers make promising cognitive models: while they use a bounded model of working memory and pursue incremental hypotheses in parallel, they still achieve...
Stephen Wu, Asaf Bachrach, Carlos Cardenas, Willia...
The predictable trajectory of underwater gliders can be used in geographic routing protocols. Factors such as drifting and localization errors cause uncertainty when estimating a g...
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...