André Uschmajew

49 papers Journal 49

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Numerically stable variants of overrelaxation for operator Sinkhorn iteration. CoRR Henrik Eisenmann, Tasuku Soma, Xun Tang, André Uschmajew
2025	J	`jnl`	Discontinuous Galerkin discretization of conservative dynamical low-rank approximation schemes for the Vlasov-Poisson equation. CoRR André Uschmajew, Andreas Zeiser
2025	J	`jnl`	Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations. Numerische Mathematik Markus Bachmayr, Henrik Eisenmann, André Uschmajew
2025	J	`jnl`	Gauss-Southwell Type Descent Methods for Low-Rank Matrix Optimization. J. Optim. Theory Appl. Guillaume Olikier, André Uschmajew, Bart Vandereycken
2025	J	`jnl`	Identifiability through special linear measurements. CoRR Fulvio Gesmundo, Alexandros Grosdos, André Uschmajew
2025	J	`jnl`	On the approximation of vector-valued functions by volume sampling. J. Complex. Daniel Kressner, Tingting Ni, André Uschmajew
2025	J	`jnl`	On the randomized SVD in infinite dimensions. CoRR Daniel Kressner, David Persson, André Uschmajew
2024	J	`jnl`	Accelerating operator Sinkhorn iteration with overrelaxation. CoRR Tasuku Soma, André Uschmajew
2024	J	`jnl`	Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Factorization. SIAM J. Optim. Antonio Bellon, Mareike Dressler, Vyacheslav Kungurtsev, Jakub Marecek, André Uschmajew
2023	J	`jnl`	Dynamical low-rank approximation of the Vlasov-Poisson equation with piecewise linear spatial boundary. CoRR André Uschmajew, Andreas Zeiser
2023	J	`jnl`	Dynamical low-rank tensor approximations to high-dimensional parabolic problems: existence and convergence of spatial discretizations. CoRR Markus Bachmayr, Henrik Eisenmann, André Uschmajew
2023	J	`jnl`	Gauss-Southwell type descent methods for low-rank matrix optimization. CoRR Guillaume Olikier, André Uschmajew, Bart Vandereycken
2023	J	`jnl`	Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP. SIAM J. Matrix Anal. Appl. Mareike Dressler, André Uschmajew, Venkat Chandrasekaran
2023	J	`jnl`	Local convergence of alternating low-rank optimization methods with overrelaxation. Numer. Linear Algebra Appl. Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
2023	J	`jnl`	On the approximation of vector-valued functions by samples. CoRR Daniel Kressner, Tingting Ni, André Uschmajew
2023	J	`jnl`	Riemannian thresholding methods for row-sparse and low-rank matrix recovery. Numer. Algorithms Henrik Eisenmann, Felix Krahmer, Max Pfeffer, André Uschmajew
2022	J	`jnl`	A Note on the Optimal Convergence Rate of Descent Methods with Fixed Step Sizes for Smooth Strongly Convex Functions. J. Optim. Theory Appl. André Uschmajew, Bart Vandereycken
2022	J	`jnl`	A note on overrelaxation in the Sinkhorn algorithm. Optim. Lett. Tobias Lehmann, Max-K. von Renesse, Alexander Sambale, André Uschmajew
2022	J	`jnl`	Editorial: High-performance tensor computations in scientific computing and data science. Frontiers Appl. Math. Stat. Edoardo Di Napoli, Paolo Bientinesi, Jiajia Li, André Uschmajew
2022	J	`jnl`	Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP. CoRR Mareike Dressler, André Uschmajew, Venkat Chandrasekaran
2022	J	`jnl`	Time-Varying Semidefinite Programming: Path Following a Burer-Monteiro Factorization. CoRR Antonio Bellon, Mareike Dressler, Vyacheslav Kungurtsev, Jakub Marecek, André Uschmajew
2021	J	`jnl`	Computing Eigenspaces With Low Rank Constraints. SIAM J. Sci. Comput. Christian Krumnow, Max Pfeffer, André Uschmajew
2021	J	`jnl`	Existence of dynamical low-rank approximations to parabolic problems. Math. Comput. Markus Bachmayr, Henrik Eisenmann, Emil Kieri, André Uschmajew
2021	J	`jnl`	Local convergence of alternating low-rank optimization methods with overrelaxation. CoRR Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
2021	J	`jnl`	Riemannian thresholding methods for row-sparse and low-rank matrix recovery. CoRR Henrik Eisenmann, Felix Krahmer, Max Pfeffer, André Uschmajew
2020	J	`jnl`	A note on overrelaxation in the Sinkhorn algorithm. CoRR Tobias Lehmann, Max-K. von Renesse, Alexander Sambale, André Uschmajew
2020	J	`jnl`	Chebyshev Polynomials and Best Rank-one Approximation Ratio. SIAM J. Matrix Anal. Appl. Andrei A. Agrachev, Khazhgali Kozhasov, André Uschmajew
2020	J	`jnl`	Existence of dynamical low-rank approximations to parabolic problems. CoRR Markus Bachmayr, Emil Kieri, André Uschmajew
2020	J	`jnl`	Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation. IEEE Trans. Neural Networks Learn. Syst. Anh-Huy Phan, Andrzej Cichocki, André Uschmajew, Petr Tichavský, George Luta, Danilo P. Mandic
2019	J	`jnl`	A Gradient Sampling Method on Algebraic Varieties and Application to Nonsmooth Low-Rank Optimization. SIAM J. Optim. Seyedehsomayeh Hosseini, André Uschmajew
2018	J	`jnl`	Alternating Least Squares as Moving Subspace Correction. SIAM J. Numer. Anal. Ivan V. Oseledets, Maxim V. Rakhuba, André Uschmajew
2018	J	`jnl`	On Orthogonal Tensors and Best Rank-One Approximation Ratio. SIAM J. Matrix Anal. Appl. Zhening Li, Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
2017	J	`jnl`	A Riemannian Gradient Sampling Algorithm for Nonsmooth Optimization on Manifolds. SIAM J. Optim. Seyedehsomayeh Hosseini, André Uschmajew
2017	J	`jnl`	Finding a low-rank basis in a matrix subspace. Math. Program. Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
2017	J	`jnl`	On orthogonal tensors and best rank-one approximation ratio. CoRR Zhening Li, Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
2017	J	`jnl`	On the interconnection between the higher-order singular values of real tensors. Numerische Mathematik Wolfgang Hackbusch, André Uschmajew
2017	J	`jnl`	Perturbation of Higher-Order Singular Values. SIAM J. Appl. Algebra Geom. Wolfgang Hackbusch, Daniel Kressner, André Uschmajew
2016	J	`jnl`	Parallel algorithms for tensor completion in the CP format. Parallel Comput. Lars Karlsson, Daniel Kressner, André Uschmajew
2016	J	`jnl`	Tensor Networks and Hierarchical Tensors for the Solution of High-Dimensional Partial Differential Equations. Found. Comput. Math. Markus Bachmayr, Reinhold Schneider, André Uschmajew
2016	J	`jnl`	Tensor Networks for Latent Variable Analysis. Part I: Algorithms for Tensor Train Decomposition. CoRR Anh Huy Phan, Andrzej Cichocki, André Uschmajew, Petr Tichavský, Gheorghe Luta, Danilo P. Mandic
2015	J	`jnl`	Convergence Results for Projected Line-Search Methods on Varieties of Low-Rank Matrices Via Łojasiewicz Inequality. SIAM J. Optim. Reinhold Schneider, André Uschmajew
2015	J	`jnl`	Finding a low-rank basis in a matrix subspace. CoRR Yuji Nakatsukasa, Tasuku Soma, André Uschmajew
2015	J	`jnl`	On Convergence of the Maximum Block Improvement Method. SIAM J. Optim. Zhening Li, André Uschmajew, Shuzhong Zhang
2014	J	`jnl`	Approximation rates for the hierarchical tensor format in periodic Sobolev spaces. J. Complex. Reinhold Schneider, André Uschmajew
2014	J	`jnl`	Convergence results for projected line-search methods on varieties of low-rank matrices via Łojasiewicz inequality. CoRR Reinhold Schneider, André Uschmajew
2014	J	`jnl`	Low-Rank Tensor Methods with Subspace Correction for Symmetric Eigenvalue Problems. SIAM J. Sci. Comput. Daniel Kressner, Michael Steinlechner, André Uschmajew
2013	J	`jnl`	On Local Convergence of Alternating Schemes for Optimization of Convex Problems in the Tensor Train Format. SIAM J. Numer. Anal. Thorsten Rohwedder, André Uschmajew
2012	J	`jnl`	Local Convergence of the Alternating Least Squares Algorithm for Canonical Tensor Approximation. SIAM J. Matrix Anal. Appl. André Uschmajew
2010	J	`jnl`	Well-posedness of convex maximization problems on Stiefel manifolds and orthogonal tensor product approximations. Numerische Mathematik André Uschmajew