Corpus ID: 227054252

Quantum Multiple Kernel Learning

@article{Vedaie2020QuantumMK,
  title={Quantum Multiple Kernel Learning},
  author={Seyed Shakib Vedaie and Moslem Noori and Jaspreet Singh Oberoi and Barry C. Sanders and Ehsan Zahedinejad},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.09694}
}
Kernel methods play an important role in machine learning applications due to their conceptual simplicity and superior performance on numerous machine learning tasks. Expressivity of a machine learning model, referring to the ability of the model to approximate complex functions, has a significant influence on its performance in these tasks. One approach to enhancing the expressivity of kernel machines is to combine multiple individual kernels to arrive at a more expressive combined kernel… Expand

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