19 search results - page 2 / 4 » Experiments in Value Function Approximation with Sparse Supp... |
ICML
2008
IEEE
14 years 6 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...
ESANN
2007
13 years 6 months ago
2007
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
ISCI
2008
13 years 5 months ago
2008
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
JMLR
2008
13 years 5 months ago
2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
TSP
2010
13 years 1 days ago
2010
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...