468 search results - page 83 / 94 » Riemannian Manifold Learning |
TSP
2010
13 years 2 months ago
2010
In this paper, we present multiple novel applications for local intrinsic dimension estimation. There has been much work done on estimating the global dimension of a data set, typi...
AIPS
2007
13 years 9 months ago
2007
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
GRC
2010
IEEE
13 years 8 months ago
2010
IEEE
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
ML
2010
ACM
13 years 2 months ago
2010
ACM
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...