Constructing informative priors using transfer learning

  title={Constructing informative priors using transfer learning},
  author={Rajat Raina and Andrew Y. Ng and Daphne Koller},
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative prior over the parameters, one that encodes useful domain knowledge. Focusing on logistic regression, we present an algorithm for automatically constructing a multivariate Gaussian prior with a full covariance matrix for a given supervised learning task. This prior relaxes a commonly used but overly simplistic… CONTINUE READING
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