Zobrazeno 1 - 10
of 185
pro vyhledávání: '"USEVICH, KONSTANTIN"'
Autor:
Usevich, Konstantin, Barthelme, Simon
Computing the eigenvectors and eigenvalues of a perturbed matrix can be remarkably difficult when the unperturbed matrix has repeated eigenvalues. In this work we show how the limiting eigenvectors and eigenvalues of a symmetric matrix $K(\varepsilon
Externí odkaz:
http://arxiv.org/abs/2407.17047
This article characterizes the rank-one factorization of auto-correlation matrix polynomials. We establish a sufficient and necessary uniqueness condition for uniqueness of the factorization based on the greatest common divisor (GCD) of multiple poly
Externí odkaz:
http://arxiv.org/abs/2308.15106
Autor:
Clausel, Marianne, Diehl, Joscha, Mignot, Raphael, Schmitz, Leonard, Sugiura, Nozomi, Usevich, Konstantin
We establish the well-definedness of the barycenter (in the sense of Buser and Karcher) for every integrable measure on the free nilpotent Lie group of step $L$ (over $\mathbb{R}^d$). We provide two algorithms for computing it, using methods from Lie
Externí odkaz:
http://arxiv.org/abs/2305.18996
Autor:
Usevich, Konstantin
In this note we consider the problem of ParaTuck-2 decomposition of a three-way tensor.We provide an algebraic algorithm for finding the ParaTuck-2 decomposition for the case when the ParaTuck-2 ranks are smaller than the frontal dimensions of the te
Externí odkaz:
http://arxiv.org/abs/2302.00922
Autor:
Borsoi, Ricardo Augusto, Lehmann, Isabell, Akhonda, Mohammad Abu Baker Siddique, Calhoun, Vince, Usevich, Konstantin, Brie, David, Adali, Tülay
Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tasks in functional Magnetic Resonance Imaging (fMRI) data. Coupled matri
Externí odkaz:
http://arxiv.org/abs/2211.14253
This work introduces a novel Fourier phase retrieval model, called polarimetric phase retrieval that enables a systematic use of polarization information in Fourier phase retrieval problems. We provide a complete characterization of uniqueness proper
Externí odkaz:
http://arxiv.org/abs/2206.12868
Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review
Autor:
Gillard, Jonathan, Usevich, Konstantin
Publikováno v:
Statistics and Its Interface, International Press, In press
In this paper we offer a review and bibliography of work on Hankel low-rank approximation and completion, with particular emphasis on how this methodology can be used for time series analysis and forecasting. We begin by describing possible formulati
Externí odkaz:
http://arxiv.org/abs/2206.05103
Gaussian process (GP) regression is a fundamental tool in Bayesian statistics. It is also known as kriging and is the Bayesian counterpart to the frequentist kernel ridge regression. Most of the theoretical work on GP regression has focused on a larg
Externí odkaz:
http://arxiv.org/abs/2201.01074
The tensor power method generalizes the matrix power method to higher order arrays, or tensors. Like in the matrix case, the fixed points of the tensor power method are the eigenvectors of the tensor. While every real symmetric matrix has an eigendec
Externí odkaz:
http://arxiv.org/abs/2111.06880
Publikováno v:
19th IFAC Symposium on System Identification, SYSID 2021, Jul 2021, Padova (virtual), Italy
We consider the problem of identifying a parallel Wiener-Hammerstein structure from Volterra kernels. Methods based on Volterra kernels typically resort to coupled tensor decompositions of the kernels. However, in the case of parallel Wiener-Hammerst
Externí odkaz:
http://arxiv.org/abs/2109.09584