کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533990 870201 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Online algorithm based on support vectors for orthogonal regression
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Online algorithm based on support vectors for orthogonal regression
چکیده انگلیسی


• We introduce a new online algorithm for orthogonal regression (OR).
• The method is constructed via a stochastic gradient descent approach.
• An incremental strategy (ISA) is introduced, which is used to find sparse solutions.
• The ISA also can be used to find the “minimal tube” containing the data.
• As far as we are aware, this is the first method for OR that uses the “kernel-trick.”

In this paper, we introduce a new online algorithm for orthogonal regression. The method is constructed via an stochastic gradient descent approach combined with the idea of a tube loss function, which is similar to the one used in support vector (SV) regression. The algorithm can be used in primal or in dual variables. The latter formulation allows the introduction of kernels and soft margins. In addition, an incremental strategy algorithm is introduced, which can be used to find sparse solutions and also an approximation to the “minimal tube” containing the data. The algorithm is very simple to implement and avoids quadratic optimization.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 34, Issue 12, 1 September 2013, Pages 1394–1404
نویسندگان
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