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In this document, a neural network is employed in order to estimate the solution of the initial value problem in the context of non linear trajectories. Such trajectories can be subject to gravity, thrust, drag, centrifugal force,…

Machine Learning · Computer Science 2021-07-21 Theodoros Ntakouris

We introduce a novel approach to reduce the computational effort of solving mixed-integer convex chance constrained programs through the scenario approach. Instead of reducing the number of required scenarios, we directly minimize the…

Optimization and Control · Mathematics 2020-02-05 Damian Frick , Pier Giuseppe Sessa , Tony A. Wood , Maryam Kamgarpour

Obstructions influence the growth and expansion of bodies in a wide range of settings -- but isolating and understanding their impact can be difficult in complex environments. Here, we study obstructed growth/expansion in a model system…

Soft Condensed Matter · Physics 2024-01-24 Abigail Plummer , Caroline Adkins , Jean-François Louf , Andrej Košmrlj , Sujit S. Datta

Certifying feasibility in decision-making, critical in many industries, can be framed as a constraint satisfaction problem. This paper focuses on characterising a subset of parameter values from an a priori set that satisfy constraints on a…

Systems and Control · Electrical Eng. & Systems 2025-11-14 Max Mowbray , Nilay Shah , Benoît Chachuat

In network flow problems, there is a well-known one-to-one relationship between extreme points of the feasibility region and trees in the associated undirected graph. The same is true for the dual differential problem. In this paper, we…

Combinatorics · Mathematics 2023-08-16 René Brandenberg , Paul Stursberg

The curse of dimensionality associated with the Hilbert space of spin systems provides a significant obstruction to the study of condensed matter systems. Tensor networks have proven an important tool in attempting to overcome this…

Quantum Physics · Physics 2017-05-17 Jacob C. Bridgeman , Christopher T. Chubb

This paper discusses an outer-approximation guided optimization method for constrained neural network inverse problems with rectified linear units. The constrained neural network inverse problems refer to an optimization problem to find the…

Optimization and Control · Mathematics 2020-02-25 Myun-Seok Cheon

We investigate the geometry of injection regions and its relationship to optimization of power flows in tree networks. The injection region is the set of all vectors of bus power injections that satisfy the network and operation…

Optimization and Control · Mathematics 2016-11-17 Javad Lavaei , David Tse , Baosen Zhang

We consider solving large scale nonconvex optimisation problems with nonnegativity constraints. Such problems arise frequently in machine learning, such as nonnegative least-squares, nonnegative matrix factorisation, as well as problems…

Optimization and Control · Mathematics 2024-05-22 Oscar Smee , Fred Roosta

Starting from three-dimensional nonlinear elasticity under the restriction of incompressibility, we derive reduced models to capture the behavior of strings in response to external forces. Our $\Gamma$-convergence analysis of the…

Analysis of PDEs · Mathematics 2023-06-22 Dominik Engl , Carolin Kreisbeck

In this paper, we introduce a method to deal with the problem of robot local path planning among pushable objects -- an open problem in robotics. In particular, we achieve that by training multiple agents simultaneously in a physics-based…

A mathematical method for through-wall imaging via wave phenomena in the time domain is introduced. The method makes use of a single reflected wave over a finite time interval and gives us a criterion whether a penetrable obstacle exists or…

Analysis of PDEs · Mathematics 2018-03-06 Masaru Ikehata

Convex optimization is a well-established research area with applications in almost all fields. Over the decades, multiple approaches have been proposed to solve convex programs. The development of interior-point methods allowed solving a…

Optimization and Control · Mathematics 2020-01-08 Ahmed Douik , Babak Hassibi

We develop a weak adversarial approach to solving obstacle problems using neural networks. By employing (generalised) regularised gap functions and their properties we rewrite the obstacle problem (which is an elliptic variational…

Optimization and Control · Mathematics 2024-11-28 Amal Alphonse , Michael Hintermüller , Alexander Kister , Chin Hang Lun , Clemens Sirotenko

In this paper, we introduce a set of tools for providing user-friendly explanations in an explanation-based constraint programming system. The idea is to represent the constraints of a problem as an hierarchy (a tree). Users are then…

Programming Languages · Computer Science 2007-05-23 Narendra Jussien , Samir Ouis

Contextual online decision-making problems with constraints appear in a wide range of real-world applications, such as adaptive experimental design under safety constraints, personalized recommendation with resource limits, and dynamic…

Machine Learning · Statistics 2025-05-23 Haichen Hu , David Simchi-Levi , Navid Azizan

Parametric path problems arise independently in diverse domains, ranging from transportation to finance, where they are studied under various assumptions. We formulate a general path problem with relaxed assumptions, and describe how this…

Data Structures and Algorithms · Computer Science 2021-06-08 Prerona Chatterjee , Kshitij Gajjar , Jaikumar Radhakrishnan , Girish Varma

In a capacitated directed graph, it is known that the set of all min-cuts forms a distributive lattice [1], [2]. Here, we describe this lattice as a regular predicate whose forbidden elements can be advanced in constant parallel time after…

Data Structures and Algorithms · Computer Science 2025-12-23 Robert Streit , Vijay K. Garg

In the \emph {barrier resilience} problem (introduced by Kumar {\em et al.}, Wireless Networks 2007), we are given a collection of regions of the plane, acting as obstacles, and we would like to remove the minimum number of regions so that…

Computational Complexity · Computer Science 2017-06-07 Matias Korman , Maarten Löffler , Rodrigo I. Silveira , Darren Strash

We develop a linear-algebraic framework for dimensional analysis in systems with constraints, particularly when variables are numerous or related by implicit relations so that direct elimination is impractical. By expressing both…

Mathematical Physics · Physics 2026-03-31 Umpei Miyamoto