Improving Random Projections Using Marginal Information

机译：使用边际信息改善随机投影

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We present an improved version of random projections that takes advantage of marginal norms. Using a maximum likelihood estimator (MLE), margin-constrained random projections can improve estimation accuracy considerably. Theoretical properties of this estimator are analyzed in detail.

机译：我们提出了利用边际范数的随机投影的改进版本。使用最大似然估计器（MLE），受边际限制的随机投影可以显着提高估计精度。对该估计量的理论性质进行了详细分析。

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来源
《Annual Conference on Learning Theory(COLT 2006); 20060622-25; Pittsburgh,PA(US)》|2006年|P.635-649|共15页
会议地点 PittsburghPA(US)
作者
Ping Li; Trevor J. Hastie; Kenneth W. Church;
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Department of Statistics, Stanford University, Stanford CA 94305, USA;

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原文格式 PDF
正文语种 eng
中图分类程序设计、软件工程;
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机译：使用边际信息改善随机投影

Improving Random Projections Using Marginal Information

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