6 search results - page 1 / 2 » Learning Functions of Few Arbitrary Linear Parameters in Hig... |
CORR
2010
Springer
13 years 3 months ago
2010
Springer
Let us assume that f is a continuous function defined on the unit ball of Rd , of the form f(x) = g(Ax), where A is a k×d matrix and g is a function of k variables for k ≪ d. ...
NIPS
1997
13 years 6 months ago
1997
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
MICCAI
2000
Springer
13 years 8 months ago
2000
Springer
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
ICIP
2003
IEEE
14 years 6 months ago
2003
IEEE
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
ALT
2004
Springer
14 years 1 months ago
2004
Springer
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...