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
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Nonlinear dimensionality reduction with relative distance comparison
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
نویسندگان
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