As a foundation for inductive inference, Bayesian statistics is attractive
because it can provide a complete prescription for learning from data.
As a practical matter many problems that we face today in learning from
data, are far more easily solved by Bayesian methods than other approaches.
Two phenomena have come together to make this happen:
 The first is
the enormous
increase in the size of databases, which has brought with it much greater
complexity in the data we must analyze; Bayesian statistics, long much
more straightforward than other approaches, is able to address,
conceptually, the complexity.

The second is tremendous advances in computational methods for Bayesian
methods that have made it feasible to compute with large databases.
Our research program in Bayesian methods addresses
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