The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Abstract—Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspect...
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
The underlying structure of why and how consumers value reliability of electric service is explored, together with the technological options and cost characteristics for the provi...
Timothy Mount, William Schulze, Richard E. Schuler
Imagine some program and a number of changes. If none of these changes is applied (“yesterday”), the program works. If all changes are applied (“today”), the program does n...