112 search results - page 4 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
122
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ICML
2005
IEEE
16 years 4 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...
138
Voted
ICML
2005
IEEE
16 years 4 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...
156
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DSMML
2004
Springer
15 years 8 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...
137
Voted
DSMML
2004
Springer
15 years 8 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...
135
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DAGM
2010
Springer
15 years 4 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...