Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation. - David M. Holloway; Francisco J. P. Lopes; Luciano da Fontoura Costa; Bruno Augusto Nassif Travençolo; Nina Golyandina; Konstantin Usevich; Alexander V. Spirov (PLoS Comput. Biol., 2011)

Variable projection methods for approximate GCD computations. - Konstantin Usevich; Ivan Markovsky (ACM Commun. Comput. Algebra, 2012)

Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability. - Nina Golyandina; David M. Holloway; Francisco J. P. Lopes; Alexander V. Spirov; Ekaterina N. Spirova; Konstantin Usevich (ICCS, 2012)

Regularized structured low-rank approximation with applications. - Mariya Ishteva; Konstantin Usevich; Ivan Markovsky (CoRR, 2013)

Structured Low-Rank Approximation with Missing Data. - Ivan Markovsky; Konstantin Usevich (SIAM J. Matrix Anal. Appl., 2013)

Nonlinearly Structured Low-Rank Approximation. - Ivan Markovsky; Konstantin Usevich (Low-Rank and Sparse Modeling for Visual Analysis, 2014)

Identification of a block-structured model with several sources of nonlinearity. - Anne Van Mulders; Laurent Vanbeylen; Konstantin Usevich (ECC, 2014)

Realization and identification of autonomous linear periodically time-varying systems. - Ivan Markovsky; Jan Goos; Konstantin Usevich; Rik Pintelon (Autom., 2014)

Optimization on a Grassmann manifold with application to system identification. - Konstantin Usevich; Ivan Markovsky (Autom., 2014)

Adjusted least squares fitting of algebraic hypersurfaces. - Konstantin Usevich; Ivan Markovsky (CoRR, 2014)

Software for weighted structured low-rank approximation. - Ivan Markovsky; Konstantin Usevich (J. Comput. Appl. Math., 2014)

Variable projection for affinely structured low-rank approximation in weighted 2-norms. - Konstantin Usevich; Ivan Markovsky (J. Comput. Appl. Math., 2014)

Factorization Approach to Structured Low-Rank Approximation with Applications. - Mariya Ishteva; Konstantin Usevich; Ivan Markovsky (SIAM J. Matrix Anal. Appl., 2014)

A Recursive Restricted Total Least-Squares Algorithm. - Stephan Rhode; Konstantin Usevich; Ivan Markovsky; Frank Gauterin (IEEE Trans. Signal Process., 2014)

A Polynomial Formulation for Joint Decomposition of Symmetric Tensors of Different Orders. - Pierre Comon; Yang Qi; Konstantin Usevich (LVA/ICA, 2015)

Quasi-Hankel low-rank matrix completion: a convex relaxation. - Konstantin Usevich; Pierre Comon (CoRR, 2015)

Optimal choice of Hankel-block-Hankel matrix shape in 2-D parameter estimation: The rank-one case. - Souleymen Sahnoun; Konstantin Usevich; Pierre Comon (EUSIPCO, 2016)

Canonical polyadic decomposition of hyperspectral patch tensors. - Miguel Angel Veganzones; Jeremy E. Cohen; Rodrigo Cabral Farias; Konstantin Usevich; Lucas Drumetz; Jocelyn Chanussot; Pierre Comon (EUSIPCO, 2016)

X-rank and identifiability for a polynomial decomposition model. - Pierre Comon; Yang Qi; Konstantin Usevich (CoRR, 2016)

Hankel Low-Rank Matrix Completion: Performance of the Nuclear Norm Relaxation. - Konstantin Usevich; Pierre Comon (IEEE J. Sel. Top. Signal Process., 2016)

High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation? - Konstantin Usevich; Souleymen Sahnoun; Pierre Comon (LVA/ICA, 2017)

Identifiability of an X-Rank Decomposition of Polynomial Maps. - Pierre Comon; Yang Qi; Konstantin Usevich (SIAM J. Appl. Algebra Geom., 2017)

Variable projection methods for approximate (greatest) common divisor computations. - Konstantin Usevich; Ivan Markovsky (Theor. Comput. Sci., 2017)

Multidimensional ESPRIT for Damped and Undamped Signals: Algorithm, Computations, and Perturbation Analysis. - Souleymen Sahnoun; Konstantin Usevich; Pierre Comon (IEEE Trans. Signal Process., 2017)

Characterization of Finite Signals with Low-Rank Stft. - Konstantin Usevich; Valentin Emiya; David Brie; Caroline Chaux (SSP, 2018)

Structured low-rank matrix completion for forecasting in time series analysis. - Jonathan Gillard 002; Konstantin Usevich (CoRR, 2018)

Globally Convergent Jacobi-Type Algorithms for Simultaneous Orthogonal Symmetric Tensor Diagonalization. - Jianze Li; Konstantin Usevich; Pierre Comon (SIAM J. Matrix Anal. Appl., 2018)

Performance Bounds for Coupled CP Model in the Framework of Hyperspectral Super-Resolution. - Clémence Prévost; Konstantin Usevich; Pierre Comon; Martin Haardt; David Brie (CAMSAP, 2019)

Software package for mosaic-Hankel structured low-rank approximation. - Konstantin Usevich; Ivan Markovsky (CDC, 2019)

Coupled Tensor Low-rank Multilinear Approximation for Hyperspectral Super-resolution. - Clémence Prévost; Konstantin Usevich; Pierre Comon; David Brie (ICASSP, 2019)

Jacobi-type algorithm for low rank orthogonal approximation of symmetric tensors and its convergence analysis. - Jianze Li; Konstantin Usevich; Pierre Comon (CoRR, 2019)

On Cramér-Rao Lower Bounds with Random Equality Constraints. - Clémence Prévost; Eric Chaumette; Konstantin Usevich; David Brie; Pierre Comon (ICASSP, 2020)

On the convergence of Jacobi-type algorithms for Independent Component Analysis. - Jianze Li; Konstantin Usevich; Pierre Comon (SAM, 2020)

Gradient based block coordinate descent algorithms for joint approximate diagonalization of matrices. - Jianze Li; Konstantin Usevich; Pierre Comon (CoRR, 2020)

Decoupling multivariate polynomials: Interconnections between tensorizations. - Konstantin Usevich; Philippe Dreesen; Mariya Ishteva (J. Comput. Appl. Math., 2020)

Approximate Matrix and Tensor Diagonalization by Unitary Transformations: Convergence of Jacobi-Type Algorithms. - Konstantin Usevich; Jianze Li; Pierre Comon (SIAM J. Optim., 2020)

Hyperspectral Super-Resolution With Coupled Tucker Approximation: Recoverability and SVD-Based Algorithms. - Clémence Prévost; Konstantin Usevich; Pierre Comon; David Brie (IEEE Trans. Signal Process., 2020)

Coupled Tensor Models Accounting for Inter-image Variability. - Ricardo Augusto Borsoi; Clémence Prévost; Konstantin Usevich; David Brie; José C. M. Bermudez; Cédric Richard (ACSCC, 2021)

A tensor-based approach for training flexible neural networks. - Yassine Zniyed; Konstantin Usevich; Sebastian Miron; David Brie (ACSCC, 2021)

Tensor-based framework for training flexible neural networks. - Yassine Zniyed; Konstantin Usevich; Sebastian Miron; David Brie (CoRR, 2021)

Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion With Inter-Image Variability. - Ricardo Augusto Borsoi; Clémence Prévost; Konstantin Usevich; David Brie; José C. M. Bermudez; Cédric Richard (IEEE J. Sel. Top. Signal Process., 2021)

Spectral Properties of Kernel Matrices in the Flat Limit. - Simon Barthelmé; Konstantin Usevich (SIAM J. Matrix Anal. Appl., 2021)

Coupled Tensor Factorization for Flow Cytometry Data Analysis. - Philippe Flores; Guillaume Harlé; Anne-Béatrice Notarantonio; Konstantin Usevich; Maud D'Aveni; Stephanie Grandemange; Marie-Thérèse Rubio; David Brie (MLSP, 2022)

Gaussian Process Regression in the Flat Limit. - Simon Barthelmé; Pierre-Olivier Amblard; Nicolas Tremblay; Konstantin Usevich (CoRR, 2022)

Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review. - Jonathan Gillard 002; Konstantin Usevich (CoRR, 2022)

Hyperspectral Super-resolution Accounting for Spectral Variability: Coupled Tensor LL1-Based Recovery and Blind Unmixing of the Unknown Super-resolution Image. - Clémence Prévost; Ricardo Augusto Borsoi; Konstantin Usevich; David Brie; José C. M. Bermudez; Cédric Richard (SIAM J. Imaging Sci., 2022)

Constrained Cramér-Rao bounds for reconstruction problems formulated as coupled canonical polyadic decompositions. - Clémence Prévost; Konstantin Usevich; Martin Haardt; Pierre Comon; David Brie (Signal Process., 2022)

Robust Eigenvectors of Symmetric Tensors. - Tommi Muller; Elina Robeva; Konstantin Usevich (SIAM J. Matrix Anal. Appl., 2022)

Low-Rank Updates of pre-trained Weights for Multi-Task Learning. - Alexandre Audibert; Massih-Reza Amini; Konstantin Usevich; Marianne Clausel (ACL (Findings), 2023)

Probability Mass Function Estimation Approaches with Application to Flow Cytometry Data Analysis. - Philippe Flores; Joseph K. Chege; Konstantin Usevich; Martin Haardt; Arie Yeredor; David Brie (CAMSAP, 2023)

Compressing Neural Networks with Two-Layer Decoupling. - Joppe De Jonghe; Konstantin Usevich; Philippe Dreesen; Mariya Ishteva (CAMSAP, 2023)

Tensor-Based Two-Layer Decoupling of Multivariate Polynomial Maps. - Konstantin Usevich; Yassine Zniyed; Mariya Ishteva; Philippe Dreesen; André L. F. de Almeida (EUSIPCO, 2023)

Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion. - R. A. Borsoi; Isabell Lehmann; Mohammad A. B. S. Akhonda; Vince D. Calhoun; Konstantin Usevich; David Brie; Tülay Adali (ICASSP, 2023)

An algebraic algorithm for rank-2 ParaTuck-2 decomposition. - Konstantin Usevich (CoRR, 2023)

On factorization of rank-one auto-correlation matrix polynomials. - Konstantin Usevich; Julien Flamant; Marianne Clausel; David Brie (CoRR, 2023)

Convergence of Gradient-Based Block Coordinate Descent Algorithms for Nonorthogonal Joint Approximate Diagonalization of Matrices. - Jianze Li; Konstantin Usevich; Pierre Comon (SIAM J. Matrix Anal. Appl., 2023)

Anomaly Detection Using Multiscale Signatures. - Raphael Mignot; Valerian Mange; Konstantin Usevich; Marianne Clausel; Jean-Yves Tourneret; François Vincent (EUSIPCO, 2024)

Computing asymptotic eigenvectors and eigenvalues of perturbed symmetric matrices. - Konstantin Usevich; Simon Barthelmé (CoRR, 2024)

The Barycenter in Free Nilpotent Lie Groups and Its Application to Iterated-Integrals Signatures. - Marianne Clausel; Joscha Diehl; Raphael Mignot; Leonard Schmitz; Nozomi Sugiura; Konstantin Usevich (SIAM J. Appl. Algebra Geom., 2024)

Polarimetric Fourier Phase Retrieval. - Julien Flamant; Konstantin Usevich; Marianne Clausel; David Brie (SIAM J. Imaging Sci., 2024)

Structured Nuclear Norm Matrix Completion: Guaranteeing Exact Recovery via Block-Column Scaling. - Konstantin Usevich; Jonathan Gillard 002; Philippe Dreesen; Ivan Markovsky (Numer. Linear Algebra Appl., 2025)

Personalized Coupled Tensor Decomposition for Multimodal Data Fusion: Uniqueness and Algorithms. - Ricardo Augusto Borsoi; Konstantin Usevich; David Brie; Tülay Adali (IEEE Trans. Signal Process., 2025)

Identifiability of Deep Polynomial Neural Networks. - Konstantin Usevich; Clara Dérand; Ricardo Augusto Borsoi; Marianne Clausel (CoRR, 2025)