Reshaped tensor nuclear norms for higher order tensor completion

We investigate optimal conditions for inducing low-rankness of higher order tensors by using convex tensor norms with reshaped tensors. propose the nuclear norm as a generalized approach to reshape be regularized norm. Furthermore, we latent combine multiple analyze generalization bounds completion models proposed and show that novel reshaping lead lower Rademacher complexities. Through simulation real-data experiments, our methods are favorably compared existing consolidating theoretical claims.