Model compensation techniques for noise-robust speech recognition approximate the corrupted speech distribution. This paper introduces a sampling method that, given speech and noi...
As an alternative to standard PCA, matrix-based image dimensionality reduction methods have recently been proposed and have gained attention due to reported computational efficie...
This paper extends basic software-testing theory to software components and adds explicit state to the theory. The resulting theory e enough to abstractly model the construction o...
In this work, we present a general method for approximating nonlinear transformations of Gaussian mixture random variables. It is based on transforming the individual Gaussians wi...
We propose a modular framework for robust 3D reconstruction from unorganized, unoriented, noisy, and outlierridden geometric data. We gain robustness and scalability over previous...
Patrick Mullen, Fernando de Goes, Mathieu Desbrun,...