22 search results - page 3 / 5 » A Sparse Kernel Density Estimation Algorithm Using Forward C... |
124
Voted
NIPS
2008
15 years 3 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
125
Voted
ECCV
2008
Springer
16 years 4 months ago
2008
Springer
We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
148
Voted
COLT
2010
Springer
15 years 7 days ago
2010
Springer
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
153
Voted
TSP
2010
14 years 9 months ago
2010
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
142
Voted
TMI
2010
14 years 9 months ago
2010
We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed...