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Bayesian Structured Prediction Using Gaussian Processes
Sebastien Bratieres, Novi Quadrianto, Zoubin Ghahramani
We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing…
Scaling the Indian Buffet Process via Submodular Maximization
Colorado Reed, Zoubin Ghahramani
Inference for latent feature models is inherently difficult as the inference space grows exponentially with the size of the input data and number of latent features. In this work,…
A dependent partition-valued process for multitask clustering and time evolving network modelling
Konstantina Palla, David A. Knowles, Zoubin Ghahramani
The fundamental aim of clustering algorithms is to partition data points. We consider tasks where the discovered partition is allowed to vary with some covariate such as space or t…
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
David Duvenaud, James Robert Lloyd, Roger Grosse +2
Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositi…