We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
When solving machine learning problems, there is currently little automated support for easily experimenting with alternative statistical models or solution strategies. This is be...
Sooraj Bhat, Ashish Agarwal, Alexander Gray, Richa...
Often, high dimensional data lie close to a low-dimensional submanifold and it is of interest to understand the geometry of these submanifolds. The homology groups of a manifold a...
Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sh...
Background: Two problems complicate the study of selection in viral genomes: Firstly, the presence of genes in overlapping reading frames implies that selection in one reading fra...
Saskia de Groot, Thomas Mailund, Gerton Lunter, Jo...
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...