首页|New Findings Reported from Georgia Institute of Technology Describe Advances in Support Vector Machines (New Equivalences Between Interpolation and Svms: Kernels and Structured Features)
New Findings Reported from Georgia Institute of Technology Describe Advances in Support Vector Machines (New Equivalences Between Interpolation and Svms: Kernels and Structured Features)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning - Support Vector Machines. According to news reporting originating from Atlanta, Georgia, by NewsRx correspondents, research stated, “The support vector machine (SVM) is a supervised learning algorithm that finds a maximum-margin linear classifier, often after mapping the data to a high-dimensional feature sp ace via the kernel trick. Recent work has demonstrated that in certain sufficiently overparameterized settings, the SVM decision function coincides exactly with the minimum-norm label interpolant.”
AtlantaGeorgiaUnited StatesNorth and Central AmericaMachine LearningSupport Vector MachinesGeorgia Institute of Technology
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