22 search results - page 1 / 5 » Sparse Convolved Gaussian Processes for Multi-output Regress... |
NIPS
2008
13 years 8 months ago
2008
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
ICCV
2011
IEEE
12 years 7 months ago
2011
IEEE
Recognition of motions and activities of objects in videos requires effective representations for analysis and matching of motion trajectories. In this paper, we introduce a new r...
JMLR
2010
13 years 1 months ago
2010
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
ECCV
2008
Springer
14 years 9 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 ...
ICML
2008
IEEE
14 years 7 months ago
2008
IEEE
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...