Variational Gaussian process classifiers

@article{Gibbs2000VariationalGP,
  title={Variational Gaussian process classifiers},
  author={Mark N. Gibbs and D. Mackay},
  journal={IEEE transactions on neural networks},
  year={2000},
  volume={11 6},
  pages={
          1458-64
        }
}
  • Mark N. Gibbs, D. Mackay
  • Published 2000
  • Mathematics, Computer Science, Medicine
  • IEEE transactions on neural networks
Gaussian processes are a promising nonlinear regression tool, but it is not straightforward to solve classification problems with them. In this paper the variational methods of Jaakkola and Jordan are applied to Gaussian processes to produce an efficient Bayesian binary classifier. 
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  • 22
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  • 5
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  • 4
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  • 44
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2
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4
5
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References

SHOWING 1-10 OF 29 REFERENCES
Regression with Gaussian processes
  • 49
  • Highly Influential
  • PDF
Gaussian Processes for Regression
  • 1,031
  • PDF
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo
  • 86
  • Highly Influential
  • PDF
Bayesian parameter estimation via variational methods
  • 562
  • PDF
Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification
  • 442
  • PDF
Flexible Non-linear Approaches to Classification
  • 63
  • Highly Influential
The Evidence Framework Applied to Classification Networks
  • D. Mackay
  • Mathematics, Computer Science
  • Neural Computation
  • 1992
  • 742
  • PDF
Computation with Infinite Neural Networks
  • 154
Computing upper and lower bounds on likelihoods in intractable networks
  • 71
  • Highly Influential
  • PDF
Pattern Recognition and Neural Networks
  • 3,727
  • Highly Influential
  • PDF
...
1
2
3
...