André Uschmajew

Publication Activity (10 Years)

Years Active: 2010-2025
Publications (10 Years): 33

Top Topics

Semidefinite Program

Thresholding Methods

Singular Values

Top Venues

SIAM J. Matrix Anal. Appl.

Publications

Daniel Kressner, Tingting Ni, André Uschmajew
On the approximation of vector-valued functions by volume sampling. J. Complex. 86 (2025)
Antonio Bellon, Mareike Dressler, Vyacheslav Kungurtsev, Jakub Marecek, André Uschmajew
Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Factorization. SIAM J. Optim. 34 (1) (2024)
Daniel Kressner, Tingting Ni, André Uschmajew
On the approximation of vector-valued functions by samples. CoRR (2023)
Markus Bachmayr, Henrik Eisenmann, André Uschmajew
Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations. CoRR (2023)
Henrik Eisenmann, Felix Krahmer, Max Pfeffer, André Uschmajew
Riemannian thresholding methods for row-sparse and low-rank matrix recovery. Numer. Algorithms 93 (2) (2023)
Guillaume Olikier, André Uschmajew, Bart Vandereycken
Gauss-Southwell type descent methods for low-rank matrix optimization. CoRR (2023)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Local convergence of alternating low-rank optimization methods with overrelaxation. Numer. Linear Algebra Appl. 30 (3) (2023)
André Uschmajew, Andreas Zeiser
Dynamical low-rank approximation of the Vlasov-Poisson equation with piecewise linear spatial boundary. CoRR (2023)
Mareike Dressler, André Uschmajew, Venkat Chandrasekaran
Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP. SIAM J. Matrix Anal. Appl. 44 (4) (2023)
Mareike Dressler, André Uschmajew, Venkat Chandrasekaran
Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP. CoRR (2022)
Antonio Bellon, Mareike Dressler, Vyacheslav Kungurtsev, Jakub Marecek, André Uschmajew
Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Factorization. CoRR (2022)
Tobias Lehmann, Max-K. von Renesse, Alexander Sambale, André Uschmajew
A note on overrelaxation in the Sinkhorn algorithm. Optim. Lett. 16 (8) (2022)
Edoardo Di Napoli, Paolo Bientinesi, Jiajia Li, André Uschmajew
Editorial: High-performance tensor computations in scientific computing and data science. Frontiers Appl. Math. Stat. 8 (2022)
André Uschmajew, Bart Vandereycken
A Note on the Optimal Convergence Rate of Descent Methods with Fixed Step Sizes for Smooth Strongly Convex Functions. J. Optim. Theory Appl. 194 (1) (2022)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Local convergence of alternating low-rank optimization methods with overrelaxation. CoRR (2021)
Henrik Eisenmann, Felix Krahmer, Max Pfeffer, André Uschmajew
Riemannian thresholding methods for row-sparse and low-rank matrix recovery. CoRR (2021)
Christian Krumnow, Max Pfeffer, André Uschmajew
Computing Eigenspaces With Low Rank Constraints. SIAM J. Sci. Comput. 43 (1) (2021)
Markus Bachmayr, Henrik Eisenmann, Emil Kieri, André Uschmajew
Existence of dynamical low-rank approximations to parabolic problems. Math. Comput. 90 (330) (2021)
Andrei A. Agrachev, Khazhgali Kozhasov, André Uschmajew
Chebyshev Polynomials and Best Rank-one Approximation Ratio. SIAM J. Matrix Anal. Appl. 41 (1) (2020)
Tobias Lehmann, Max-K. von Renesse, Alexander Sambale, André Uschmajew
A note on overrelaxation in the Sinkhorn algorithm. CoRR (2020)
Anh-Huy Phan, Andrzej Cichocki, André Uschmajew, Petr Tichavský, George Luta, Danilo P. Mandic
Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation. IEEE Trans. Neural Networks Learn. Syst. 31 (11) (2020)
Markus Bachmayr, Emil Kieri, André Uschmajew
Existence of dynamical low-rank approximations to parabolic problems. CoRR (2020)
Seyedehsomayeh Hosseini, André Uschmajew
A Gradient Sampling Method on Algebraic Varieties and Application to Nonsmooth Low-Rank Optimization. SIAM J. Optim. 29 (4) (2019)
Zhening Li, Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
On Orthogonal Tensors and Best Rank-One Approximation Ratio. SIAM J. Matrix Anal. Appl. 39 (1) (2018)
Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
Alternating Least Squares as Moving Subspace Correction. SIAM J. Numer. Anal. 56 (6) (2018)
Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
Finding a low-rank basis in a matrix subspace. Math. Program. 162 (1-2) (2017)
Seyedehsomayeh Hosseini, André Uschmajew
A Riemannian Gradient Sampling Algorithm for Nonsmooth Optimization on Manifolds. SIAM J. Optim. 27 (1) (2017)
Wolfgang Hackbusch, André Uschmajew
On the interconnection between the higher-order singular values of real tensors. Numerische Mathematik 135 (3) (2017)
Wolfgang Hackbusch, Daniel Kressner, André Uschmajew
Perturbation of Higher-Order Singular Values. SIAM J. Appl. Algebra Geom. 1 (1) (2017)
Zhening Li, Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
On orthogonal tensors and best rank-one approximation ratio. CoRR (2017)
Anh Huy Phan, Andrzej Cichocki, André Uschmajew, Petr Tichavský, Gheorghe Luta, Danilo P. Mandic
Tensor Networks for Latent Variable Analysis. Part I: Algorithms for Tensor Train Decomposition. CoRR (2016)
Lars Karlsson, Daniel Kressner, André Uschmajew
Parallel algorithms for tensor completion in the CP format. Parallel Comput. 57 (2016)
Markus Bachmayr, Reinhold Schneider, André Uschmajew
Tensor Networks and Hierarchical Tensors for the Solution of High-Dimensional Partial Differential Equations. Found. Comput. Math. 16 (6) (2016)
Reinhold Schneider, André Uschmajew
Convergence Results for Projected Line-Search Methods on Varieties of Low-Rank Matrices Via Łojasiewicz Inequality. SIAM J. Optim. 25 (1) (2015)
Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
Finding a low-rank basis in a matrix subspace. CoRR (2015)
Zhening Li, André Uschmajew, Shuzhong Zhang
On Convergence of the Maximum Block Improvement Method. SIAM J. Optim. 25 (1) (2015)
Daniel Kressner, Michael Steinlechner, André Uschmajew
Low-Rank Tensor Methods with Subspace Correction for Symmetric Eigenvalue Problems. SIAM J. Sci. Comput. 36 (5) (2014)
Reinhold Schneider, André Uschmajew
Convergence results for projected line-search methods on varieties of low-rank matrices via Łojasiewicz inequality. CoRR (2014)
Reinhold Schneider, André Uschmajew
Approximation rates for the hierarchical tensor format in periodic Sobolev spaces. J. Complex. 30 (2) (2014)
Thorsten Rohwedder, André Uschmajew
On Local Convergence of Alternating Schemes for Optimization of Convex Problems in the Tensor Train Format. SIAM J. Numer. Anal. 51 (2) (2013)
André Uschmajew
Local Convergence of the Alternating Least Squares Algorithm for Canonical Tensor Approximation. SIAM J. Matrix Anal. Appl. 33 (2) (2012)
André Uschmajew
Well-posedness of convex maximization problems on Stiefel manifolds and orthogonal tensor product approximations. Numerische Mathematik 115 (2) (2010)