activity
20162025
most citedSolving piecewise linear equations in abs-normal form

41 citations · 73 across the 14 of their papers we have counts for

collaborators

19 papers

cs.LG2025

Synthetic Data Generation and Differential Privacy using Tensor Networks' Matrix Product States (MPS)

Alejandro Moreno R., Desale Fentaw, Samuel Palmer +7

Synthetic data generation is a key technique in modern artificial intelligence, addressing data scarcity, privacy constraints, and the need for diverse datasets in training robust…

quant-ph2025

Quantum reinforcement learning in dynamic environments

Oliver Sefrin, Manuel Radons, Lars Simon +1

Combining quantum computing techniques in the form of amplitude amplification with classical reinforcement learning has led to the so-called "hybrid agent for quantum-accessible re…

quant-ph2024

Introducing the Kernel Descent Optimizer for Variational Quantum Algorithms

Lars Simon, Holger Eble, Manuel Radons

In recent years, variational quantum algorithms have garnered significant attention as a candidate approach for near-term quantum advantage using noisy intermediate-scale quantum (…

quant-ph2024

Denoising Gradient Descent in Variational Quantum Algorithms

Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1

In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\e…

quant-ph2023★ 1 cited

Interpolating Parametrized Quantum Circuits using Blackbox Queries

Lars Simon, Holger Eble, Hagen-Henrik Kowalski +1

This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials. We develop two algorithms for the con…

cs.LG2023★ 1 cited

Algorithms for the Training of Neural Support Vector Machines

Lars Simon, Manuel Radons

Neural support vector machines (NSVMs) allow for the incorporation of domain knowledge in the design of the model architecture. In this article we introduce a set of training algor…

quant-ph2023

On Neural Quantum Support Vector Machines

Lars Simon, Manuel Radons

In \cite{simon2023algorithms} we introduced four algorithms for the training of neural support vector machines (NSVMs) and demonstrated their feasibility. In this note we introduce…

math.MG2021

Edge-unfolding nested prismatoids

Manuel Radons

A -Prismatoid is the convex hull of two convex polygons and which lie in parallel planes . Let be the orthogonal projection of onto…

math.NA2020

Convergence results for some piecewise linear solvers

Manuel Radons, Siegfried M. Rump

Let be a real matrix and . The piecewise linear equation system is called an \textit{absolute value equation}. We consider…

math.OC2019★ 6 cited

Generalized Perron Roots and Solvability of the Absolute Value Equation

Manuel Radons, Josué Tonelli-Cueto

Let be a real matrix. The piecewise linear equation system is called an absolute value equation (AVE). It is well-known to be equivalent to the…

math.OC2018

An Open Newton Method for Piecewise Smooth Functions

Manuel Radons, Lutz Lehmann, Tom Streubel +1

Recent research has shown that piecewise smooth (PS) functions can be approximated by piecewise linear functions with second order error in the distance to a given reference point.…

math.OC2018

Semi-automatically optimized calibration of internal combustion engines

Timo Burggraf, Michael Joswig, Marc E. Pfetsch +2

Modern combustion engines incorporate a number of actuators and sensors that can be used to control and optimize the performance and emissions. We describe a semi-automatic method…

math.NA2017★ 1 cited

Sign controlled solvers for the absolute value equation with an application to support vector machines

Lutz Lehmann, Manuel Radons, Siegfried M. Rump +1

Let be a real matrix and . The piecewise linear equation system is called an absolute value equation. It is equivalent to…

math.OC2017

A note on surjectivity of piecewise affine mappings

Manuel Radons

A standard theorem in nonsmooth analysis states that a piecewise affine function is surjective if it is coherently oriented in that the linear…

math.NA2017★ 41 cited

Solving piecewise linear equations in abs-normal form

Andreas Griewank, Jens Uwe Bernt, Manuel Radons +1

With the ultimate goal of iteratively solving piecewise smooth (PS) systems, we consider the solution of piecewise linear (PL) equations. PL models can be derived in the fashion of…

math.NA2017★ 1 cited

Integrating Lipschitzian Dynamical Systems using Piecewise Algorithmic Differentiation

Andreas Griewank, Richard Hasenfelder, Manuel Radons +1

In this article we analyze a generalized trapezoidal rule for initial value problems with piecewise smooth right hand side \(F:\R^n\to\R^n\). When applied to such a problem the cla…

math.NA2017

Piecewise linear secant approximation via Algorithmic Piecewise Differentiation

Andreas Griewank, Tom Streubel, Lutz Lehmann +2

It is shown how piecewise differentiable functions that are defined by evaluation programs can be approximated locally by a piecewise linear m…

math.OC2016★ 22 cited

Direct solution of piecewise linear systems

Manuel Radons

Let be a real matrix, , and the componentwise modulus of . Then the piecewise linear equation system is call…

math.NA2016

working precision inverses for symmetric tridiagonal Toeplitz matrices with floating point calculations

Manuel Radons

A well known numerical task is the inversion of large symmetric tridiagonal Toeplitz matrices, i.e., matrices whose entries equal on the diagonal and on the extra diagonals…