A unifying framework for vector-valued manifold regularization and multi-view learning

@inproceedings{Minh2013AUF,
  title={A unifying framework for vector-valued manifold regularization and multi-view learning},
  author={Ha Quang Minh and Loris Bazzani and Vittorio Murino},
  booktitle={ICML},
  year={2013}
}
This paper presents a general vector-valued reproducing kernel Hilbert spaces (RKHS) formulation for the problem of learning an unknown functional dependency between a structured input space and a structured output space, in the Semi-Supervised Learning setting. Our formulation includes as special cases Vector-valued Manifold Regularization and Multi-view Learning, thus provides in particular a unifying framework linking these two important learning approaches. In the case of least square loss… CONTINUE READING
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