Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes
Bayesian approaches to preference learning using Gaussian Processes (GPs) are attractive due to their ability to explicitly model uncertainty in users' latent utility functions; unfortunately existing techniques have cubic time complexity in the number of
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|Source:||IJCAI International Joint Conference on Artificial Intelligence|
|01_Abbasnejad_Learning_Community-Based_2013.pdf||534.67 kB||Adobe PDF||Request a copy|
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