The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions hav...
Despite their simplicity, scalar threshold operators effectively remove additive white Gaussian noise from wavelet detail coefficients of many practical signals. This paper explor...
Alyson K. Fletcher, Vivek K. Goyal, Kannan Ramchan...
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
We describe a detailed experimental investigation of the phase transition for several different classes of randomly generated satisfiability problems. We observe a remarkable consi...
This paper presents the theoretical background for the Model Based Underdetermined Source Separation presented in [5]. We show that for a given frequency band, in contrast to custo...