Max-Margin Learning of Gaussian Mixtures with Sequential Minimal Optimization
نویسندگان
چکیده
This works deals with discriminant training of Gaussian Mixture Models through margin maximization. We go one step further previous work, we propose a new formulation of the learning problem that allows the use of efficient optimization algorithm popularized for Support Vector Machines, yielding improved convergence properties and recognition accuracy on handwritten digits recognition.
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