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AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes · Xavi Gonzalvo · Vitaly Kuznetsov · Mehryar Mohri · Scott Yang
We present a new framework for analyzing and learning artificial neural networks. Our approach simultaneously and adaptively learns both the structure of the network as well as its weights. The methodology is based upon and accompanied by strong data-dependent theoretical learning guarantees, so that the final network architecture provably adapts to the complexity of any given problem.
Summary/NotesAuthor Information
Corinna Cortes (Google Research)
Xavi Gonzalvo (Google Inc.)
Vitaly Kuznetsov (Google)
Mehryar Mohri (Courant Institute and Google Research)
Scott Yang (Courant Institute)
Related Events (a corresponding poster, oral, or spotlight)
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2017 Poster: AdaNet: Adaptive Structural Learning of Artificial Neural Networks »
Mon. Aug 7th 08:30 AM -- 12:00 PM Room Gallery #121
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