A reliable and unobtrusive measurement of working memory load could be used to evaluate the efficacy of interfaces and to provide real-time user-state information to adaptive syst...
David B. Grimes, Desney S. Tan, Scott E. Hudson, P...
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
: This paper presents a classifier that is based on a modified version of the well known K-Nearest Neighbors classifier (K-NN). The original K-NN classifier was adjusted to work wi...