【摘 要】
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This talk is about how to learn representations of data sampled on a graph,where the graph geometry can be leveraged to facilitate pattern recognition tasks
【出 处】
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2016数学青年学者论坛(2016 Young Mathematician Forum)
论文部分内容阅读
This talk is about how to learn representations of data sampled on a graph,where the graph geometry can be leveraged to facilitate pattern recognition tasks.Particularly,we will introduce "Haar scattering net" as a model of unsupervised deep networks.While Mallats scattering transform employs continuous wavelets and applies to images and audio signals,Haar scattering net uses Haar wavelets and is applicable to discrete data types.
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