The paper defines a lexicographic total order on complex numbers and a Spectral and Nilpotent Ordering (SNO) for arbitrary matrices, claiming to extend majorization, Schur-Ostrowski, and operator convexity results to the complex domain.
Random Double Tensors Integrals
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abstract
In this work, we try to build a theory for random double tensor integrals (DTI). We begin with the definition of DTI and discuss how randomness structure is built upon DTI. Then, the tail bound of the unitarily invariant norm for the random DTI is established and this bound can help us to derive tail bounds of the unitarily invariant norm for various types of two tensors means, e.g., arithmetic mean, geometric mean, harmonic mean, and general mean. By associating DTI with perturbation formula, i.e., a formula to relate the tensor-valued function difference with respect the difference of the function input tensors, the tail bounds of the unitarily invariant norm for the Lipschitz estimate of tensor-valued function with random tensors as arguments are derived for vanilla case and quasi-commutator case, respectively. We also establish the continuity property for random DTI in the sense of convergence in the random tensor mean, and we apply this continuity property to obtain the tail bound of the unitarily invariant norm for the derivative of the tensor-valued function.
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Matrix Ordering through Spectral and Nilpotent Structures in Totally Ordered Complex Number Fields
The paper defines a lexicographic total order on complex numbers and a Spectral and Nilpotent Ordering (SNO) for arbitrary matrices, claiming to extend majorization, Schur-Ostrowski, and operator convexity results to the complex domain.