In this paper, we propose the concept of Manifold of Facial Expression based on the observation that images of a subject’s facial expressions define a smooth manifold in the hig...
Scientists find that the human perception is based on the similarity on the manifold of data set. Isometric feature mapping (Isomap) is one of the representative techniques of man...
Jie Chen, Ruiping Wang, Shiguang Shan, Wen Gao, Xi...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...