We consider a class of holographic tensor networks that are efficiently contractible variational ansatze, manifestly (approximate) quantum error correction codes, and can support power-law correlation functions. In the case when network consists single type also acts as an erasure code, we show it cannot be both locally sustain Motivated by this no-go theorem, desirability local contractibility...

Often, we work with vector spaces which consists of an appropriate. Many concepts concerning vectors in Rn can be extended to other mathematical systems. We can think of a vector space in.of a finite-dimensional nontrivial proper subspace of such a vector space is equivalent to ACA0 over RCA0. This paper is a continuation of 3.Subspaces of Vector Spaces. A subspace W of a vector space V is a su...

Hyperspectral image (HSI) clustering is a challenging task due to the high complexity of HSI data. Subspace has been proven be powerful for exploiting intrinsic relationship between data points. Despite impressive performance in clustering, traditional subspace methods often ignore inherent structural information among In this article, we revisit with graph convolution and present novel framewo...

This paper presents a new subspace modeling and selection approach for noisy speech recognition. In subspace modeling, we develop factor analysis (FA) for representing noisy speech. FA is a data generation model where the common factors are extracted with factor loading matrix and specific factors. We bridge the connection of FA to signal subspace (SS) approach. Interestingly, FA partitions noi...