Balanced relay allocation on heterogeneous unstructured overlays

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This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...

The method of moments (MOM), as introduced by Roger F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (IE) formulations applied to both electrostatic (part 1) and electrodynamic or full-wave problem ...

The method of moments (MOM), as introduced by R. F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (PIE) formulations applied to both electrostatic (part 1) and electrodynamic, or full-wave, problem ...

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applicati ...

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Estimating the stress of reinforcing bars and its variations in service conditions can be useful to determine the reserve capacity of structures or to assess the risk of fatigue in the reinforcement. This paper investigates the use crack width measurements ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ...

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

We introduce two new approximation methods for the numerical evaluation of the long-range component of the range-separated Coulomb potential and the approximation of the resulting high dimensional Two-Electron Integrals tensor (TEI) with long-range interac ...

Network neutrality is important for users, content providers, policymakers, and regulators interested in understanding how network providers differentiate performance. When determining whether a network differentiates against certain traffic, it is importa ...

This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...

Balanced relay allocation on heterogeneous unstructured overlays

Chattez avec Graph Search

A ride time-oriented scheduling algorithm for dial-a-ride problems

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

From low-rank retractions to dynamical low-rank approximation and back

Roger F. Harrington and the Method of Moments: Part 2: Electrodynamics

Roger F. Harrington and the Method of Moments: Part 1: Electrostatics

Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

Adaptive projected variational quantum dynamics

Gibbs sampling the posterior of neural networks

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Estimation of the bar stress based on crack width measurements in reinforced concrete structures

Reliable data-driven decision-making through optimal transport

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Bayesian reconstruction of memories stored in neural networks from their connectivity

Results on Sparse Integer Programming and Geometric Independent Sets

Approximation Algorithms for Allocation and Network Design

Factorized structure of the long-range two-electron integrals tensor and its application in quantum chemistry

Localizing Traffic Differentiation

Estimating the Topology of Preferential Attachment Graphs Under Partial Observability