Representative Selection with Structured Sparsity

We propose a novel formulation to find representatives in data samples via learning with structured sparsity. To find representatives with both diversity and representativeness, we formulate the problem as a structurally-regularized learning where the objective function consists of a reconstruction...

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Main Authors: Wang, Hongxing, Kawahara, Yoshinobu, Weng, Chaoqun, Yuan, Junsong
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2017
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在線閱讀:https://hdl.handle.net/10356/82103
http://hdl.handle.net/10220/43501
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