کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
530044 869733 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nyström-based approximate kernel subspace learning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Nyström-based approximate kernel subspace learning
چکیده انگلیسی


• We propose a method for determining a subspace of the kernel space.
• We follow an approximate kernel learning approach for fast calculations.
• We test our approach in nonlinear large-scale classification problems.

In this paper, we describe a method for the determination of a subspace of the feature space in kernel methods, which is suited to large-scale learning problems. Linear model learning in the obtained space corresponds to a nonlinear model learning process in the input space. Since the obtained feature space is determined only by exploiting properties of the training data, this approach can be used for generic nonlinear pattern recognition. That is, nonlinear data mapping can be considered to be a pre-processing step exploiting nonlinear relationships between the training data. Linear techniques can be subsequently applied in the new feature space and, thus, they can model nonlinear properties of the problem at hand. In order to appropriately address the inherent problem of kernel learning methods related to their time and memory complexities, we follow an approximate learning approach. We show that the method can lead to considerable operation speed gains and achieve very good performance. Experimental results verify our analysis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 57, September 2016, Pages 190–197
نویسندگان
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