8 papers
Iterative solvers for partial differential equations with dissipative structure: Operator preconditioning and optimal control
Volker Mehrmann, Manuel Schaller, Martin Stoll
This work considers the iterative solution of large-scale problems subject to non-symmetric matrices or operators arising in discretizations of (port-)Hamiltonian partial different…
KEEP: Integrating Medical Ontologies with Clinical Data for Robust Code Embeddings
Ahmed Elhussein, Paul Meddeb, Abigail Newbury +3
Machine learning in healthcare requires effective representation of structured medical codes, but current methods face a trade off: knowledge graph based approaches capture formal…
Fast and Simple Multiclass Data Segmentation: An Eigendecomposition and Projection-Free Approach
Chiara Faccio, Margherita Porcelli, Francesco Rinaldi +1
Graph-based machine learning has seen an increased interest over the last decade with many connections to other fields of applied mathematics. Learning based on partial differentia…
Low-rank computation of the posterior mean in Multi-Output Gaussian Processes
Sebastian Esche, Martin Stoll
Gaussian processes (GP) are a versatile tool in machine learning and computational science. We here consider the case of multi-output Gaussian processes (MOGP) and present low-rank…
Preconditioned Additive Gaussian Processes with Fourier Acceleration
Theresa Wagner, Tianshi Xu, Franziska Nestler +2
Gaussian processes (GPs) are crucial in machine learning for quantifying uncertainty in predictions. However, their associated covariance matrices, defined by kernel functions, are…
Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
Theresa Wagner, Franziska Nestler, Martin Stoll
One of the main computational bottlenecks when working with kernel based learning is dealing with the large and typically dense kernel matrix. Techniques dealing with fast approxim…
A splitting-based KPIK method for eddy current optimal control problems in an all-at-once approach
Min-Li Zeng, Martin Stoll
In this paper, we focus on efficient methods to solve discretized linear systems obtained from eddy current optimal control problems in an all-at-once approach. We construct a new…
A Preconditioned Interior Point Method for Support Vector Machines Using an ANOVA-Decomposition and NFFT-Based Matrix-Vector Products
Theresa Wagner, John W. Pearson, Martin Stoll
In this paper we consider the numerical solution to the soft-margin support vector machine optimization problem. This problem is typically solved using the SMO algorithm, given the…