inJournal
2023
Repository Open Access
Alessandra Bernardi, Claudia De Lazzari and Fulvio Gesmundo
Dimension of tensor network varieties
inJournal
2023
Repository Open Access
Paul Breiding, Fulvio Gesmundo , Mateusz Michałek and Nick Vannieuwenhoven
Algebraic compressed sensing
inJournal
2023
Repository Open Access
Mareike Dressler, André Uschmajew and Venkat Chandrasekaran
Kronecker product approximation of operators in spectral norm via alternating SDP
Henrik Eisenmann and André Uschmajew
Maximum relative distance between real rank-two and rank-one tensors
Henrik Eisenmann , Felix Krahmer , Max Pfeffer and André Uschmajew
Riemannian thresholding methods for row-sparse and low-rank matrix recovery
Ivan V. Oseledets, Maxim Rakhuba and André Uschmajew
Local convergence of alternating low-rank optimization methods with overrelaxation
Arthur Bik and Henrik Eisenmann
The geometries of Jordan nets and Jordan webs
Austin Conner, Fulvio Gesmundo , Joseph M. Landsberg and Emanuele Ventura
Rank and border rank of Kronecker powers of tensors and Strassen's laser method
Edoardo Di Napoli, Paolo Bientinesi, Jiajia Li and André Uschmajew
Editorial : High-performance tensor computations in scientific computing and data science
Academic
2022
Repository Open Access
Henrik Eisenmann
Multilinear optimization in low-rank models
Henrik Eisenmann and Yuji Nakatsukasa
Solving two-parameter eigenvalue problems using an alternating method
Fulvio Gesmundo and Chiara Meroni
The geometry of discotopes
Tobias Lehmann, Max von Renesse, Alexander Sambale and André Uschmajew
A note on overrelaxation in the Sinkhorn algorithm
André Uschmajew and Bart Vandereycken
A note on the optimal convergence rate of descent methods with fixed step sizes for smooth strongly convex functions
inJournal
2021
Repository Open Access
Markus Bachmayr, Henrik Eisenmann , Emil Kieri and André Uschmajew
Existence of dynamical low-rank approximations to parabolic problems
Arthur Bik, Henrik Eisenmann and Bernd Sturmfels
Jordan algebras of symmetric matrices
Taylor Brysiewicz and Fulvio Gesmundo
The degree of Stiefel manifolds
inJournal
2021
Repository Open Access
Matthias Christandl, Fulvio Gesmundo , Mateusz Michałek and Jeroen Zuiddam
Border rank non-additivity for higher order tensors
inJournal
2021
Repository Open Access
Matthias Christandl, Fulvio Gesmundo , Daniel Stilck França and Albert H. Werner
Optimization at the boundary of the tensor network variety
Wolfgang Hackbusch and André Uschmajew
Modified iterations for data-sparse solution of linear systems
inJournal
2021
Repository Open Access
Christian Krumnow , Max Pfeffer and André Uschmajew
Computing eigenspaces with low rank constraints
inJournal
2020
Repository Open Access
Andrei Agrachev, Khazhgali Kozhasov and André Uschmajew
Chebyshev polynomials and best rank-one approximation ratio
Martin Eigel, Manuel Marschall, Max Pfeffer and Reinhold Schneider
Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations
inJournal
2020
Repository Open Access
André Uschmajew , Markus Bachmayr, Henrik Eisenmann and Emil Kieri
Dynamical low-rank approximation for parabolic problems [In: Mini-workshop : computational optimization on manifolds ; 15 November - 21 November 2020 ; report no. 36/2020]
André Uschmajew and Bart Vandereycken
Geometric methods on low-rank matrix and tensor manifolds
André Uschmajew and Bart Vandereycken
On critical points of quadratic low-rank matrix optimization problems
inJournal
2019
Repository Open Access
Seyedehsomayeh Hosseini and André Uschmajew
A gradient sampling method on algebraic varieties and application to nonsmooth low-rank optimization
Seyedehsomayeh Hosseini, Boris S. Mordukhovich and André Uschmajew (Eds.)
Nonsmooth optimization and its applications : based on the workshop 'Nonsmooth optimization and its Applications', Bonn, Germany, May 15-19, 2017
inBook
2019
Repository Open Access
Seyedehsomayeh Hosseini, D. Russell Luke and André Uschmajew
Tangent and normal cones for low-rank matrices
Max Pfeffer , André Uschmajew , Adriana Amaro and Ulrich Pfeffer
Data fusion techniques for the integration of multi-domain genomic data from uveal melanoma
inJournal
2019
Repository Open Access
Max Pfeffer , Anna Seigal and Bernd Sturmfels
Learning paths from signature tensors
inJournal
2018
Repository Open Access
Zhening Li, Yuji Nakatsukasa , Tasuku Soma and André Uschmajew
On orthogonal tensors and best rank-one approximation ratio
inJournal
2018
Repository Open Access
Ivan V. Oseledets, Maxim Rakhuba and André Uschmajew
Alternating least squares as moving subspace correction
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