Sparse Representation for Gaussian Process Models

Csató, Lehel, Opper, Manfred

Dec-31-2001–Neural Information Processing Systems

We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets.

artificial intelligence, bayesian inference, vector, (18 more...)

Neural Information Processing Systems

Dec-31-2001

Conferences PDF

Country:
- Europe > United Kingdom (0.28)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning
      - Learning Graphical Models > Directed Networks
        Bayesian Learning (0.69)
      - Statistical Learning (0.71)
    - Representation & Reasoning > Uncertainty
      - Bayesian Inference (0.69)
  - Modeling & Simulation (0.88)

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