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ICML
2005
IEEE
14 years 9 months ago
Preference learning with Gaussian processes
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...
Wei Chu, Zoubin Ghahramani
ICML
2005
IEEE
14 years 9 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
NIPS
2007
13 years 10 months ago
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
We introduce a functional representation of time series which allows forecasts to be performed over an unspecified horizon with progressively-revealed information sets. By virtue...
Nicolas Chapados, Yoshua Bengio
ESANN
2006
13 years 10 months ago
A Gaussian process latent variable model formulation of canonical correlation analysis
Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
Gayle Leen, Colin Fyfe
NIPS
2004
13 years 10 months ago
Semi-supervised Learning via Gaussian Processes
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
Neil D. Lawrence, Michael I. Jordan