We propose a kernel propagation strategy (KPS) for out-of-sample projections. •. We develop a specific kernel propagation algorithm based on KPS. •. Extensive ...

Since KMO is difficult to compute out-of-sample projections for kernel subspace learning, we propose a kernel propagation strategy (KPS) based on data ...

Kernel matrix optimization (KMO) aims at learning appropriate kernel matrices by solving a certain opti- mization problem rather than using empirical kernel ...

Kernel propagation strategy: A novel out-of-sample propagation projection for subspace learning. https://doi.org/10.1016/j.jvcir.2016.01.007 · Full text.

We propose a kernel propagation strategy (KPS) for out-of-sample projections.We develop a specific kernel propagation algorithm based on KPS.

We propose a kernel propagation strategy (KPS) for out-of-sample projections.We develop a specific kernel propagation algorithm based on KPS.

Kernel propagation strategy: A novel out-of-sample propagation projection for subspace learning. January 2016 · Journal of Visual Communication and Image ...

We propose a kernel propagation strategy (KPS) for out-of-sample projections. We develop a specific kernel propagation algorithm based on KPS. Extensive ...

... kernel learning" by M. Baghshah et al ... Kernel propagation strategy: A novel out-of-sample propagation projection for subspace learning ... novel weightedkernel k ...

Kernel propagation strategy: A novel out-of-sample propagation projection for subspace learning. Article. Jan 2016; J VIS COMMUN IMAGE R. Shuzhi Su · Hongwei Ge ...