74 search results - page 13 / 15 » Learning sparse metrics via linear programming |
VLSISP
2010
13 years 4 months ago
2010
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
ICML
2005
IEEE
14 years 6 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
TVCG
2012
11 years 8 months ago
2012
—The issue of transferring facial performance from one person’s face to another’s has been an area of interest for the movie industry and the computer graphics community for ...
SODA
2010
ACM
14 years 3 months ago
2010
ACM
The minimum latency problem (MLP) is a well-studied variant of the traveling salesman problem (TSP). In the MLP, the server's goal is to minimize the average latency that the...
ICML
2002
IEEE
14 years 6 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...