Publications related to The sliding Frank-Wolfe algorithm and its application to super-resolution microscopy

Related publications (45)

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

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

Boosting Resource-Constrained Federated Learning Systems with Guessed Updates

Mohamed Yassine Boukhari, Anne-Marie Kermarrec, Rafael Pereira Pires, Rishi Sharma, Akash Balasaheb Dhasade

Federated learning (FL) enables a set of client devices to collaboratively train a model without sharing raw data. This process, though, operates under the constrained computation and communication resources of edge devices. These constraints combined with ...

Institute of Electrical and Electronics Engineers (IEEE)2025

Exploiting Covalent Chemical Labeling with Self-Labeling Proteins

Kai Johnsson

The visualization and manipulation of proteins in live cells are critical for studying complex biological processes. Self-labeling proteins do so by enabling the specific and covalent attachment of synthetic probes, offering unprecedented flexibility in th ...

Annual Reviews2025

Bioanode engineering for living solar cells

Charlotte Elisabeth Marie Roullier

Whole-cell biophotovoltaic (BPV) devices leverage photoautotrophic microorganisms like cyanobacteria to convert sunlight and water into bioelectricity. They are capable of growing on sequestered carbon dioxide (CO2), eliminating the need to add exogenous o ...

EPFL2025

Engineering Symmetry Breaking Interfaces by Nanoscale Structural-Energetics in Orthorhombic Perovskite Thin Films

Duncan Thomas Lindsay Alexander, Bernat Mundet

The atomic configuration of phases and their interfaces is fundamental to materials design and engineering. Here, we unveil a transition metal oxide interface, whose formation is driven by energetic influences─epitaxial tensile strain versus oxygen octahed ...

2025

A learning-based approach to stochastic optimal control under reach-avoid constraint

Maryam Kamgarpour, Tingting Ni

We develop a model-free approach to optimally control stochastic, Markovian systems subject to a reach-avoid constraint. Specifically, the state trajectory must remain within a safe set while reaching a target set within a finite time horizon. Due to the t ...

Association for Computing Machinery2025

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Alexandra Cameron Karpilow

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

EPFL2024

Significant reduction of cell invasiveness in nanoneedle insertion into a living cell with an electron-beam-deposited probe: impacts of probe geometry, speed and vibration

Marcos Penedo Garcia

Intracellular probing of living cells using atomic force microscopy (AFM) has advanced significantly, but it requires specially designed nanoprobes to achieve precision and minimize damage. The development of focused ion beam (FIB)-milled nanoprobes enable ...

2025

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

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

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 ...

Pergamon-Elsevier Science Ltd2024

Lamellar Schwann Cells in the Pacinian Corpuscle Potentiate Vibration Perception

Graham Knott, Mary-Claude Croisier-Coeytaux, Jérôme Blanc, Stéphanie Clerc

Pacinian corpuscles are among the most sensitive mechanoreceptors found in vertebrates, and they are tuned to vibrations in the highest perceptible frequency range (100 to 2000 Hz). One of their anatomical hallmarks is the onion-like cell layers surroundin ...

AMER ASSOC ADVANCEMENT SCIENCE2025

Passivating oxidation behavior of Ti0.12Al0.21B0.67 coatings investigated by scanning transmission electron microscopy and chemical environment dependent density functional theory simulations

Johann Michler

The oxidation behavior of stoichiometric Ti0.12Al0.21B0.67 coatings is investigated by scanning transmission electron microscopy (STEM) after oxidizing for 1, 4 and 8 h at 700 degrees C and at 800 and 900 degrees C. In the as deposited state, a similar to ...

PERGAMON-ELSEVIER SCIENCE LTD2025

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

A Multiscale Bayesian Approach to Quantification and Denoising of Energy-dispersive X-ray Data

Cécile Hébert, Duncan Thomas Lindsay Alexander, Pau Torruella Besa

Energy dispersive x-ray (EDX) spectrum imaging yields compositional information with a spatial resolution down to the atomic level. However, experimental limitations often produce extremely sparse and noisy EDX spectra. Under such conditions, every detecte ...

IOP Publishing Ltd2025

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

Analytical Computation of the Sensitivity Coefficients in Hybrid AC/DC Networks

Mario Paolone, Willem Lambrichts

In this paper, we present a model for the analytical computation of the power flow sensitivity coefficients (SCs) for hybrid AC/DC networks. The SCs are defined as the partial derivates of the nodal voltages with respect to the active and reactive power in ...

2024

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 constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Live-cell imaging powered by computation

Suliana Manley

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Nature Portfolio2024

A scaling limit of the 2D parabolic Anderson model with exclusion interaction

Martin Hairer

We consider the (discrete) parabolic Anderson model ∂u(t, x)/∂t = ∆u(t, x) + ξt(x)u(t, x), t ≥ 0, x ∈ Z d. Here, the ξ-field is R-valued, acting as a dynamic random environment, and ∆ represents the discrete Laplacian. We focus on the case where ξ is given ...

Institute of Mathematical Statistics2025

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024