112 search results - page 4 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
73
Voted
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
105
Voted
DSMML
2004
Springer
15 years 2 months ago
2004
Springer
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...
92
Voted
DSMML
2004
Springer
15 years 2 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
DAGM
2010
Springer
14 years 10 months ago
2010
Springer
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...