We present a semi-parametric latent variable model based technique for density modelling, dimensionality reduction and visualization. Unlike previous methods, we estimate the late...
We present two extensions of the algorithm by Broomhead et al [2] which is based on the idea that singular values that scale linearly with the radius of the data ball can be explo...
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...
Blocking probabilities in Wavelength Division Multiplex optical networks are hard to compute for realistic sized systems, even though analytical formulas for the distribution exis...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...