This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Background: Automatic annotation of sequenced eukaryotic genomes integrates a combination of methodologies such as ab-initio methods and alignment of homologous genes and/or prote...
Alan Christoffels, Richard Bartfai, Hamsa Srinivas...
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...