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What is Regularized Gradient Boosting Algorithm about?

The document presents a new algorithm called Regularized Gradient Boosting (RGB) that enhances the traditional Gradient Boosting method by incorporating regularization and deriving data-dependent learning guarantees based on Rademacher complexities. It emphasizes the importance of selecting base predictors that balance empirical fit and complexity, and introduces a scalable implementation inspired by Randomized Coordinate Descent. Experimental results demonstrate that RGB outperforms standard Gradient Boost

Author

connarthian

Language

EN