Gradient Boosting on Stochastic Data Streams

1 Mar 2017Hanzhang HuWen SunArun VenkatramanMartial HebertJ. Andrew Bagnell

Boosting is a popular ensemble algorithm that generates more powerful learners by linearly combining base models from a simpler hypothesis class. In this work, we investigate the problem of adapting batch gradient boosting for minimizing convex loss functions to online setting where the loss at each iteration is i.i.d sampled from an unknown distribution... (read more)

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