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Lockout: Sparse Regularization of Neural Networks
Many regression and classification procedures fit a parameterized function $f(x;w)$ of predictor variables $x$ to data $\{x_{i}, y_{i}\}_1^N$ based on some loss criterion $L(y, f)$.
Targeted transfer learning to improve performance in small medical physics datasets
The growing use of Machine Learning has produced significant advances in many fields.
Conditional Super Learner
In this article we consider the Conditional Super Learner (CSL), an algorithm which selects the best model candidate from a library conditional on the covariates.
Tree-Structured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees
Additive models, such as produced by gradient boosting, and full interaction models, such as classification and regression trees (CART), are widely used algorithms that have been investigated largely in isolation.
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