44 search results - page 2 / 9 » Approximation Bounds for Some Sparse Kernel Regression Algor... |
IDEAL
2004
Springer
13 years 10 months ago
2004
Springer
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
IJON
2007
13 years 5 months ago
2007
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
NIPS
2007
13 years 6 months ago
2007
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
IJON
2007
13 years 5 months ago
2007
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
SODA
2008
ACM
13 years 6 months ago
2008
ACM
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...