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Gradient Boosted Feature Selection
A feature selection algorithm should ideally satisfy four conditions: reliably extract relevant features; be able to identify non-linear feature interactions; scale linearly with the number of features and dimensions; allow the incorporation of known sparsity structure.
Gradient Regularized Budgeted Boosting
As machine learning transitions increasingly towards real world applications controlling the test-time cost of algorithms becomes more and more crucial.
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