Parallel Coordinates are a powerful method for visualizing multidimensional data, however, with large data sets they can become cluttered and difficult to read. On the other hand...
Elena Fanea, M. Sheelagh T. Carpendale, Tobias Ise...
Finding rapidly suitable experts in an organization to compose a team able to solve specific tasks is a typical problem in large consulting firms. In this paper we present a Des...
Simona Colucci, Tommaso Di Noia, Eugenio Di Sciasc...
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...