# Practical Bayesian Optimization of Machine Learning Algorithms

In this work, we consider the automatic tuning problem within the framework of Bayesian optimization, in which a learning algorithm's generalization performance is modeled as a sample from a Gaussian process (GP).

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# Factoring nonnegative matrices with linear programs

The constraints are chosen to ensure that the matrix C selects features; these features can then be used to find a low-rank NMF of X.

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