Multiple Kernel Learning for Dimensionality Reduction


In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting data representations are typically high-dimensional and assume diverse forms. Hence, finding a way of transforming them into a unified space of lower dimension generally facilitates… (More)
DOI: 10.1109/TPAMI.2010.183
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