EasyMKL: a scalable multiple kernel learning algorithm

  title={EasyMKL: a scalable multiple kernel learning algorithm},
  author={Fabio Aiolli and Michele Donini},
The goal of Multiple Kernel Learning (MKL) is to combine kernels derived from multiple sources in a data-driven way with the aim to enhance the accuracy of a target kernel machine. State-of-the-art methods of MKL have the drawback that the time required to solve the associated optimization problem grows (typically more than linearly) with the number of kernels to combine. Moreover, it has been empirically observed that even sophisticated methods often do not significantly outperform the simple… CONTINUE READING
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