Analyzing high-dimensional data and finding hidden patterns is a difficult problem and has attracted numerous research efforts. Automated methods can be useful to some extent but bringing the data analyst into the loop via interactive visual tools can help the discovery process tremendously. An inherent problem in this effort is that humans lack the mental capacity to truly understand spaces ex...

The performance of Krylov subspace eigenvalue algorithms for large matrices can be measured by the angle between a desired invariant subspace and the Krylov subspace. We develop general bounds for this convergence that include the effects of polynomial restarting and impose no restrictions concerning the diagonalizability of the matrix or its degree of nonnormality. Associated with a desired se...

In many real world applications data is collected in multi-dimensional spaces, with the knowledge hidden in subspaces (i.e., subsets of the dimensions). It is an open research issue to select meaningful subspaces without any prior knowledge about such hidden patterns. Standard approaches, such as pairwise correlation measures, or statistical approaches based on entropy, do not solve this proble...

By a famous result, functions in backward shift invariant subspaces in Hardy spaces are characterized by the fact that they admit a pseudocontinuation a.e. on T. More can be said if the spectrum of the associated inner function has holes on T. Then the functions of the invariant subspaces even extend analytically through these holes. We will discuss the situation in weighted backward shift inva...

the main result of this article is that for collections of entry-wise non-negative matrices the property of possessing a standard triangularization is stable under approximation. the methodology introduced to prove this result allows us to offer quick proofs of the corresponding results of [b. r. yahaghi, near triangularizability implies triangularizability, canad. math. bull. 47, (2004), no. 2...

Given a set of functions, we prove the existence of an optimal collection of subspaces minimizing the sum of the square of the distances between each function and its closest subspace in the collection. This collection of subspaces gives the best sparse representation for the given data, in a sense defined in the paper, and provides an optimal model for sampling in union of subspaces. The resul...

In this paper, we investigate the regularized inner product between meromorphic modular forms from certain distinguished subspaces. particular, compute degenerate parts of these subspaces and furthermore determine on some remaining quotient spaces.