News & Activities
- Research Topic on High-Performance Tensor Computations in Scientific Computing and Data Science
in Frontiers in Applied Mathematics and Statistics.
- Workshop: Hierarchical Numerical Methods for PDEs
September 28-29, 2021 at MPI Leipzig
- Mathematics of Data Initiative at MPI MiS
Please check for the regular seminars, courses and workshops.
The research in our group focuses on low-rank matrix and tensor approximation, with emphasis on numerical tensor calculus, nonlinear optimization methods, underlying approximability principles, as well as algebraic and geometric foundations. Our goal is to obtain a deeper understanding of low-rank models and methods, and their successful use in scientific computing and modern applications. Some keywords:
- Tensors: geometry of low-rank varieties, tensor networks, higher-order singular values, tensor product operators
- Approximation: functional analytic foundations, approximation rates, singular value estimates, spectral and nuclear norm
- Optimization: block coordinate methods, truncated iterations, Riemannian optimization, rank adaptivity, optimization landscape
- Applications: high-dimensional linear equations and eigenvalue problems, signal processing, dynamical low-rank approximation