Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Independent Factor Analysis (IFA) is a well known method used to recover independent components from their linear observed mixtures without any knowledge on the mixing process. Su...
The nature of map generalization may be non-uniform along the length of an individual line, requiring the application of methods that adapt to the local geometry and the geographi...