Multi-task Gaussian Process Prediction (2008)
Bonilla, Edwin V., Chai, Kian Ming, Williams, Christopher
In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features and a ``free-form''...
Kernel Multi-task Learning using Task-specific Features (2007)
Bonilla, Edwin V., Agakov, Felix, Williams, Christopher
In this paper we are concerned with multi-task learning when task-specific features are available. We describe two ways of achieving this using Gaussian process predictors: in the first method, the...
Predictive Search Distributions (2006)
Bonilla, Edwin V., Williams, Christopher, Agakov, Felix, Cavazos, John, Thompson, John, O'Boyle, Michael F. P.
Estimation of Distribution Algorithms (EDAs) are a popular approach to learn a probability distribution over the "good" solutions to a combinatorial optimization problem. Here we consider the case...