Solving ℓ^p-norm regularization with tensor kernels

07/18/2017
by   Saverio Salzo, et al.
0

In this paper, we discuss how a suitable family of tensor kernels can be used to efficiently solve nonparametric extensions of ℓ^p regularized learning methods. Our main contribution is proposing a fast dual algorithm, and showing that it allows to solve the problem efficiently. Our results contrast recent findings suggesting kernel methods cannot be extended beyond Hilbert setting. Numerical experiments confirm the effectiveness of the method.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset