Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
We address the problem of classification of EEG recordings for the detection of epileptic seizures. We assume that the EEG measurements can be described by a low dimensional manif...
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes...
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...
In this paper we consider modeling data lying on multiple continuous manifolds. In particular, we model the shape manifold of a person performing a motion observed from different ...