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The Introduction of Kernel Tricks in SVMs (1996)

    Bernhard Schölkopf and other researchers standardized the use of kernel functions within Support Vector Machines, allowing algorithms to effortlessly map low-dimensional data into infinite-dimensional spaces to find optimal linear decision boundaries without excessive computational cost.

    Part of the 30 AI Roots Facts: The Era of Supercomputing & Deep Learning Seeds (1996–2000) archive. HistoricallyVerified

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