102 search results - page 1 / 21 » Robust Regularized Kernel Regression |
TSMC
2008
13 years 4 months ago
2008
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
This paper presents a non-local kernel regression (NL-KR) method for image and video restoration tasks, which exploits both the non-local self-similarity and local structural regul...
NN
2010
Springer
12 years 11 months ago
2010
Springer
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
NIPS
2004
13 years 6 months ago
2004
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
IJON
2007
13 years 4 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 ...