We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Background: The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase...
Steven N. Steinway, Ruth Dannenfelser, Christopher...
In this paper logical techniques developed to formalise the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to...
Frances M. T. Brazier, Joeri Engelfriet, Jan Treur
—Detection of the number of sinusoids embedded in noise is a fundamental problem in statistical signal processing. Most parametric methods minimize the sum of a data fit (likeli...