Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. The methods can be u...
Jin Hyeong Park, Zhenyue Zhang, Hongyuan Zha, Rang...
We present a data-driven technique for generating the precomputed radiance transfer vectors of an animated character as a function of its joint angles. We learn a linear model for...
Derek Nowrouzezahrai, Patricio D. Simari, Evangelo...
To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales a...
— Today's innovations in the automotive sector are, to a great extent, based on electronics. The increasing integration complexity and stringent cost reduction goals turn E/...