576 search results - page 36 / 116 » Structured metric learning for high dimensional problems |
TEC
2010
14 years 4 months ago
2010
A new algorithm for solving MAX-SAT problems is introduced which clusters good solutions, and restarts the search from the closest feasible solution to the centroid of each cluster...
IEEECIT
2005
IEEE
15 years 3 months ago
2005
IEEE
Similarity search leveraging distance-based index structures is increasingly being used for complex data types. It has been shown that for high dimensional uniform vectors with si...
SDM
2004
SIAM
14 years 11 months ago
2004
SIAM
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
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ECML
2007
Springer
15 years 3 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
IJON
2010
14 years 7 months ago
2010
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...