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Algorithms for Hyper-Parameter Optimization

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Figure

Figure 1: The pseudo-code of generic Sequential Model-Based Optimization.
Table 1: Distribution over DBN hyper-parameters for random sampling. Options separated by “or”
Figure 2: Deep Belief Network (DBN) performance according to random search. Random search is used to explore up to 32 hyper-parameters (see Table 1)
Table 2: The test set classification error of the best model found by each search  rithm on each problem
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