306 citations · 308 across the 8 of their papers we have counts for
8 papers
A Time-aware tensor decomposition for tracking evolving patterns
Christos Chatzis, Max Pfeffer, Pedro Lind +1
Time-evolving data sets can often be arranged as a higher-order tensor with one of the modes being the time mode. While tensor factorizations have been successfully used to capture…
A weighted subspace exponential kernel for support tensor machines
Kirandeep Kour, Sergey Dolgov, Peter Benner +2
High-dimensional data in the form of tensors are challenging for kernel classification methods. To both reduce the computational complexity and extract informative features, kernel…
The cone of completely positive matrices
Max Pfeffer, Jose Alejandro Samper
We study the cone of completely positive (cp) matrices for the first interesting case . This is a semialgebraic set, which means that the polynomial equalities and inequliti…
Particle Number Conservation and Block Structures in Matrix Product States
Markus Bachmayr, Michael Götte, Max Pfeffer
The eigenvectors of the particle number operator in second quantization are characterized by the block sparsity of their matrix product state representations. This is shown to gene…
Riemannian thresholding methods for row-sparse and low-rank matrix recovery
Henrik Eisenmann, Felix Krahmer, Max Pfeffer +1
In this paper, we present modifications of the iterative hard thresholding (IHT) method for recovery of jointly row-sparse and low-rank matrices. In particular a Riemannian version…
Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations
Martin Eigel, Manuel Marschall, Max Pfeffer +1
Stochastic Galerkin methods for non-affine coefficient representations are known to cause major difficulties from theoretical and numerical points of view. In this work, an adaptiv…
Learning Paths from Signature Tensors
Max Pfeffer, Anna Seigal, Bernd Sturmfels
Matrix congruence extends naturally to the setting of tensors. We apply methods from tensor decomposition, algebraic geometry and numerical optimization to this group action. Given…
Tensor product methods and entanglement optimization for ab initio quantum chemistry
Szilárd Szalay, Max Pfeffer, Valentin Murg +4
The treatment of high-dimensional problems such as the Schrödinger equation can be approached by concepts of tensor product approximation. We present general techniques that can be…