Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging

NeurIPS 2012 Chris HinrichsVikas SinghJiming PengSterling Johnson

Multiple Kernel Learning (MKL) generalizes SVMs to the setting where one simultaneously trains a linear classifier and chooses an optimal combination of given base kernels. Model complexity is typically controlled using various norm regularizations on the vector of base kernel mixing coefficients... (read more)

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