Matrix-based Kernel Method for Large-scale Data Set
نویسندگان
چکیده
منابع مشابه
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ω e >(x−y)μ(ω) Since μ is positive we can use it to draw i.i.d. samples ωi ∼ μ which allows us to define a random feature map such that φ(x) = [φ1(x) . . . φd(x)], where φi(x) = cos(ω> i x + bi) (where bi ∼ Uniform[0, 2π]). Let k̂(x, y) = ∑d i k̂i(x, y) = 1 d ∑d i φi(x)φi(y) > = 1 dφ(x)φ(y) >. This is a standard construction; see [2, 3] for more details. Let X be a fixed data matrix N × p corresp...
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ژورنال
عنوان ژورنال: International Journal of Image, Graphics and Signal Processing
سال: 2010
ISSN: 2074-9074,2074-9082
DOI: 10.5815/ijigsp.2010.02.01