This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
We present an approach to high-level shape editing that adapts the structure of the shape while maintaining its global characteristics. Our main contribution is a new algebraic mo...
Martin Bokeloh, Michael Wand, Hans-Peter Seidel, V...
Asynchronous data communication mechanisms (ACMs) have been extensively studied as data connectors between independently timed concurrent processes. In previous work, two automati...
This paper describes a simple method for significantly improving Tandem features used to train acoustic models for large-vocabulary speech recognition. The linear activations at ...
: The paper proposes a lossy compression mechanism for 3D models (3D meshes) by improving existing compression mechanism such as progressive meshes and single refinement mesh compr...