44 search results - page 4 / 9 » Approximation Bounds for Some Sparse Kernel Regression Algor... |
AIA
2007
13 years 8 months ago
2007
Kernel Ridge Regression (KRR) and the recently developed Kernel Aggregating Algorithm for Regression (KAAR) are regression methods based on Least Squares. KAAR has theoretical adv...
IJCNN
2006
IEEE
14 years 22 days ago
2006
IEEE
Abstract— This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a pre...
JMLR
2010
13 years 1 months ago
2010
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
SIAMJO
2008
13 years 6 months ago
2008
We show that the optimal complexity of Nesterov's smooth first-order optimization algorithm is preserved when the gradient is only computed up to a small, uniformly bounded er...
NIPS
2007
13 years 8 months ago
2007
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...