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Hanzhang Hu

2 accepted papers

2019

Efficient Forward Architecture Search

NeurIPS 2019poster

We propose a neural architecture search (NAS) algorithm, Petridish, to iteratively add shortcut connections to existing network layers. The added shortcut connections effectively perform gradient boosting on the augmented layers. The proposed algorithm is motivated by the feature selection algorit…

2017

Gradient Boosting on Stochastic Data Streams

AISTATS 2017poster

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 ea…

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