کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
410634 | 679154 | 2009 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Nonlinear dimensionality reduction with relative distance comparison
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
This paper proposes a new algorithm for nonlinear dimensionality reduction. Our basic idea is to explore and exploit the local geometry of the manifold with relative distance comparisons. All such comparisons derived from local neighborhoods are enumerated to constrain the manifold to be learned. The task is formulated as a problem of quadratically constrained quadratic programming (QCQP). However, such a QCQP problem is not convex. We relax it to be a problem of semi-definite programming (SDP), from which a globally optimal embedding is obtained. Experimental results illustrate the validity of our algorithm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 7–9, March 2009, Pages 1719–1731
Journal: Neurocomputing - Volume 72, Issues 7–9, March 2009, Pages 1719–1731
نویسندگان
Chunxia Zhang, Shiming Xiang, Feiping Nie, Yangqiu Song,