Konstantin Usevich

Orcid: 0000-0002-1154-5909

According to our database1, Konstantin Usevich authored at least 57 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Polarimetric Fourier Phase Retrieval.
SIAM J. Imaging Sci., March, 2024

2023
Convergence of Gradient-Based Block Coordinate Descent Algorithms for Nonorthogonal Joint Approximate Diagonalization of Matrices.
SIAM J. Matrix Anal. Appl., June, 2023

On factorization of rank-one auto-correlation matrix polynomials.
CoRR, 2023

An algebraic algorithm for rank-2 ParaTuck-2 decomposition.
CoRR, 2023

Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion.
Proceedings of the IEEE International Conference on Acoustics, 2023

Tensor-Based Two-Layer Decoupling of Multivariate Polynomial Maps.
Proceedings of the 31st European Signal Processing Conference, 2023

Compressing Neural Networks with Two-Layer Decoupling.
Proceedings of the 9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2023

Probability Mass Function Estimation Approaches with Application to Flow Cytometry Data Analysis.
Proceedings of the 9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2023

Low-Rank Updates of pre-trained Weights for Multi-Task Learning.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Robust Eigenvectors of Symmetric Tensors.
SIAM J. Matrix Anal. Appl., December, 2022

Constrained Cramér-Rao bounds for reconstruction problems formulated as coupled canonical polyadic decompositions.
Signal Process., 2022

Hyperspectral Super-resolution Accounting for Spectral Variability: Coupled Tensor LL1-Based Recovery and Blind Unmixing of the Unknown Super-resolution Image.
SIAM J. Imaging Sci., 2022

Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review.
CoRR, 2022

Gaussian Process Regression in the Flat Limit.
CoRR, 2022

Coupled Tensor Factorization for Flow Cytometry Data Analysis.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

2021
Spectral Properties of Kernel Matrices in the Flat Limit.
SIAM J. Matrix Anal. Appl., 2021

Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion With Inter-Image Variability.
IEEE J. Sel. Top. Signal Process., 2021

Tensor-based framework for training flexible neural networks.
CoRR, 2021

A tensor-based approach for training flexible neural networks.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

Coupled Tensor Models Accounting for Inter-image Variability.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Hyperspectral Super-Resolution With Coupled Tucker Approximation: Recoverability and SVD-Based Algorithms.
IEEE Trans. Signal Process., 2020

Approximate Matrix and Tensor Diagonalization by Unitary Transformations: Convergence of Jacobi-Type Algorithms.
SIAM J. Optim., 2020

Decoupling multivariate polynomials: Interconnections between tensorizations.
J. Comput. Appl. Math., 2020

Gradient based block coordinate descent algorithms for joint approximate diagonalization of matrices.
CoRR, 2020

On the convergence of Jacobi-type algorithms for Independent Component Analysis.
Proceedings of the 11th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020

On Cramér-Rao Lower Bounds with Random Equality Constraints.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Jacobi-type algorithm for low rank orthogonal approximation of symmetric tensors and its convergence analysis.
CoRR, 2019

Coupled Tensor Low-rank Multilinear Approximation for Hyperspectral Super-resolution.
Proceedings of the IEEE International Conference on Acoustics, 2019

Software package for mosaic-Hankel structured low-rank approximation.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Performance Bounds for Coupled CP Model in the Framework of Hyperspectral Super-Resolution.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
Globally Convergent Jacobi-Type Algorithms for Simultaneous Orthogonal Symmetric Tensor Diagonalization.
SIAM J. Matrix Anal. Appl., 2018

Structured low-rank matrix completion for forecasting in time series analysis.
CoRR, 2018

Characterization of Finite Signals with Low-Rank Stft.
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

2017
Multidimensional ESPRIT for Damped and Undamped Signals: Algorithm, Computations, and Perturbation Analysis.
IEEE Trans. Signal Process., 2017

Variable projection methods for approximate (greatest) common divisor computations.
Theor. Comput. Sci., 2017

Identifiability of an X-Rank Decomposition of Polynomial Maps.
SIAM J. Appl. Algebra Geom., 2017

High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?
Proceedings of the Latent Variable Analysis and Signal Separation, 2017

2016
Hankel Low-Rank Matrix Completion: Performance of the Nuclear Norm Relaxation.
IEEE J. Sel. Top. Signal Process., 2016

X-rank and identifiability for a polynomial decomposition model.
CoRR, 2016

Canonical polyadic decomposition of hyperspectral patch tensors.
Proceedings of the 24th European Signal Processing Conference, 2016

Optimal choice of Hankel-block-Hankel matrix shape in 2-D parameter estimation: The rank-one case.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
Quasi-Hankel low-rank matrix completion: a convex relaxation.
CoRR, 2015

A Polynomial Formulation for Joint Decomposition of Symmetric Tensors of Different Orders.
Proceedings of the Latent Variable Analysis and Signal Separation, 2015

2014
A Recursive Restricted Total Least-Squares Algorithm.
IEEE Trans. Signal Process., 2014

Factorization Approach to Structured Low-Rank Approximation with Applications.
SIAM J. Matrix Anal. Appl., 2014

Variable projection for affinely structured low-rank approximation in weighted 2-norms.
J. Comput. Appl. Math., 2014

Software for weighted structured low-rank approximation.
J. Comput. Appl. Math., 2014

Adjusted least squares fitting of algebraic hypersurfaces.
CoRR, 2014

Optimization on a Grassmann manifold with application to system identification.
Autom., 2014

Realization and identification of autonomous linear periodically time-varying systems.
Autom., 2014

Identification of a block-structured model with several sources of nonlinearity.
Proceedings of the 13th European Control Conference, 2014

Nonlinearly Structured Low-Rank Approximation.
Proceedings of the Low-Rank and Sparse Modeling for Visual Analysis, 2014

2013
Structured Low-Rank Approximation with Missing Data.
SIAM J. Matrix Anal. Appl., 2013

Regularized structured low-rank approximation with applications.
CoRR, 2013

2012
Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability.
Proceedings of the International Conference on Computational Science, 2012

Variable projection methods for approximate GCD computations.
ACM Commun. Comput. Algebra, 2012

2011
Gene Expression Noise in Spatial Patterning: <i>hunchback</i> Promoter Structure Affects Noise Amplitude and Distribution in <i>Drosophila</i> Segmentation.
PLoS Comput. Biol., 2011


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