We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces fo...
Let P be a property of undirected graphs. We consider the following problem: given a graph G that has property P, nd a minimal spanning subgraph of G with property P. We describe ...
Xiaofeng Han, Pierre Kelsen, Vijaya Ramachandran, ...
This paper analyzes the application of Moran's index and Geary's coefficient to the characterization of lung nodules as malignant or benign in computerized tomography ima...