Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
We outline a distributed codingtechnique for images captured from sensors with overlapping fields of view in a sensor network. First, images from correlated views are roughly regi...
Intuitively, learning should be easier when the data points lie on a low-dimensional submanifold of the input space. Recently there has been a growing interest in algorithms that ...
We present a system to segment the medial edges of the vocal folds from stroboscopic video. The system has two components. The first learns a color transformation that optimally d...
Sonya Allin, John M. Galeotti, George D. Stetten, ...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...