Publications associées à A Box-Spline Framework for Inverse Problems With Continuous-Domain Sparsity Constraints

Publications associées (14)

K-space physics-informed neural network (k-PINN) for compressed spectral mapping and efficient inversion of vibrations in thin composite laminates

The vibrational response of structural components carries valuable information about their underlying mechanical properties, health status and operational conditions. This underscores the need for the development of efficient physics-based inversion algori ...

Elsevier BV2025

2025 roadmap on 3D nanomagnetism

Dirk Grundler

The transition from planar to three-dimensional (3D) magnetic nanostructures represents a significant advancement in both fundamental research and practical applications, offering vast potential for next-generation technologies like ultrahigh-density stora ...

IOP Publishing Ltd2025

Reduced basis method for the elastic scattering by multiple shape-parametric open arcs in two dimensions

Fernando José Henriquez Barraza

We consider the elastic scattering problem by multiple disjoint arcs or cracks in two spatial dimensions. A key aspect of our approach lies in the parametric description of each arc's shape, which is controlled by a potentially high-dimensional, possibly c ...

EDP SCIENCES S A2025

Generalization of Noisy SGD in Unbounded Non-convex Settings

Volkan Cevher, Leello Tadesse Dadi

We study the generalization of iterative noisy gradient schemes on smooth non-convex losses. Formally, we establish time-independent information theoretic generalization bounds for Stochastic Gradient Langevin Dynamics (SGLD) that do not diverge as the ite ...

2025

On decentralized computation of the leader's strategy in bi-level games

Nikolaos Geroliminis, Marko Maljkovic

Motivated by the omnipresence of hierarchical structures in many real-world applications, this study delves into the intricate realm of bi-level games, with a specific focus on exploring local Stackelberg equilibria as a solution concept. While existing li ...

2025

Riemannian acceleration with preconditioning for symmetric eigenvalue problems

Nian Shao

The analysis of the acceleration behavior of gradient-based eigensolvers with preconditioning presents a substantial theoretical challenge. In this work, we present a novel framework for preconditioning on Riemannian manifolds and introduce a metric, the l ...

Springer2025

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

Michel Bierlaire

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

2025

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Thibaut Stoltz, Jan Skaloud, Davide Antonio Cucci, Laurent Valentin Jospin, Kyriaki Mouzakidou

The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

International Society for Photogrammetry and Remote Sensing2025

On the Trade-off between Flatness and Optimization in Distributed Learning

Ali H. Sayed, Ying Cao

Institute of Electrical and Electronics Engineers2025

Maximum Radiation Efficiency of Arbitrarily Shaped Implantable Antennas

Erik Ralf Algarp, Anja Skrivervik, Mingxiang Gao

Performance limitations for implanted antennas, taking radiation efficiency as the metric, are presented. The performance limitations use a convex optimization procedure with the current density inside the implant acting as its degree of freedom. The knowl ...

2024

DISTRIBUTIONAL EXTENSION AND INVERTIBILITY OF THE k-PLANE TRANSFORM AND ITS DUAL

Michaël Unser, Rahul Parhi

We investigate the distributional extension of the k-plane transform in Rd and of related operators. We parameterize the k-plane domain as the Cartesian product of the Stiefel manifold of orthonormal k-frames in Rd with Rd-k. This parameterization imposes ...

2024

Workforce Allocation for Social Engagement Services via Stochastic Optimization

Michel Bierlaire

Social Engagement is a novel business model whose goal is transforming final users of a service from passive components into active ones. In this framework, people are contacted by the decision-maker (generally a company) and they are asked to perform task ...

Springer Science and Business Media Deutschland GmbH2024

Understanding generalization and robustness in modern deep learning

Maksym Andriushchenko

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

EPFL2024

Stochastic Risk-driven Bidding of a Solar and Storage Aggregator in Primary Frequency and Energy Markets: A Performance-based Capacity Allocation Approach

Sidi-Rachid Cherkaoui

The ever-increasing impact of deploying renewable energy resources reducing power system inertia, requires distributed energy resource (DER) aggregators to secure high-performance, fast-responding primary frequency reserve (PFR) in ancillary service market ...

2024