1235 search results - page 178 / 247 » Learning with Idealized Kernels |
NIPS
2001
13 years 11 months ago
2001
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
ICML
2008
IEEE
14 years 10 months ago
2008
IEEE
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
ICML
2008
IEEE
14 years 10 months ago
2008
IEEE
We have developed a new Linear Support Vector Machine (SVM) training algorithm called OCAS. Its computational effort scales linearly with the sample size. In an extensive empirica...
ICML
2008
IEEE
14 years 10 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...