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The Introduction of Kernel PCA (2002)

    Mathematicians standardized Kernel Principal Component Analysis, allowing algorithms to extract non-linear structural features from highly complex data dimensions without losing essential pattern variances.

    Part of the 30 AI Roots Facts: The Mobile Revolution & Big Data Explosion (2001–2005) archive. HistoricallyVerified

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