Average polynomial time for eigenvector computations

Abstract

We describe two algorithms for the eigenvalue, eigenvector problem which, on input a Gaussian matrix with complex entries, finish with probability 1 and in average polynomial time.

References in corpus (2)

• Complexity of sparse polynomial solving: homotopy on toric varieties and the condition metric
• Adaptative Step Size Selection for Homotopy Methods to Solve Polynomial Equations

Cited by in corpus (1)

• Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation