Publications associées à Parallel faceted imaging in radio interferometry via proximal splitting (Faceted HyperSARA) - II. Code and real data proof of concept

Publications associées (15)

Diffusion Moving-Average Adaptation Over Networks

Recently, the diffusion moving-average (D-MA) scheme has been proposed as a way to combat noisy links over adaptive networks. However, the current theoretical results focus on networks with mean-square error costs where the optimal local solution agrees wi ...

2024

Results on Sparse Integer Programming and Geometric Independent Sets

Jana Tabea Cslovjecsek

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 ...

EPFL2023

Aligning random graphs with a sub-tree similarity message-passing algorithm

Lenka Zdeborová, Giovanni Piccioli

The problem of aligning Erdos-Renyi random graphs is a noisy, average-case version of the graph isomorphism problem, in which a pair of correlated random graphs is observed through a random permutation of their vertices. We study a polynomial time message- ...

IOP Publishing Ltd2022

Implicit Gradient Alignment in Distributed and Federated Learning

Martin Jaggi, Yatin Dandi, Luis Felipe Barba Flores

A major obstacle to achieving global convergence in distributed and federated learning is the misalignment of gradients across clients, or mini-batches due to heterogeneity and stochasticity of the distributed data. In this work, we show that data heteroge ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Nirupam Gupta

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Faster Monotone Min-Plus Product, Range Mode, and Single Source Replacement Paths

Adam Teodor Polak

One of the most basic graph problems, All-Pairs Shortest Paths (APSP) is known to be solvable in n^{3-o(1)} time, and it is widely open whether it has an O(n^{3-ε}) time algorithm for ε > 0. To better understand APSP, one often strives to obtain subcubic t ...

Schloss Dagstuhl -- Leibniz-Zentrum für Informatik2021

Passenger-centric timetable rescheduling: A user equilibrium approach

Michel Bierlaire, Shadi Sharif Azadeh, Mohammad Yousef Maknoon, Stefan Yves Gabriel Binder

Unexpected disruptions commonly occur in the railway network, causing delays, and extra cost for operators and inconvenience for passengers by missing their connection and facing overcrowded trains. This paper presents a passenger-centric approach for time ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Editorial: Health and Performance Assessment in Winter Sports

Kamiar Aminian

FRONTIERS MEDIA SA2021

Second International Workshop on Algorithmic Bias in Search and Recommendation (bias@ecir2021)

Mirko Marras

Providing efficient and effective search and recommendation algorithms has been traditionally the main objective for the industrial and academic research communities. However, recent studies have shown that optimizing models through these algorithms may re ...

Springer Nature2021

Efficient Parsing with Derivatives and Zippers

Romain Edelmann

Parsing is the process that enables a computer system to make sense of raw data. Parsing is common to almost all computer systems: It is involved every time sequential data is read and elaborated into structured data. The theory of parsing usually focuses ...

EPFL2021

The SONATA data format for efficient description of large-scale network models

Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, James Gonzalo King, Jean-Denis Georges Emile Courcol, Judit Planas Carbonell, Michael Emiel Gevaert, Juan Bautista Hernando Vieites, Adrien Michel Achille Devresse

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation ...

2020

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks

Volkan Cevher, Fabian Ricardo Latorre Gomez, Paul Thierry Yves Rolland, Shaul Nadav Hallak

We demonstrate two new important properties of the 1-path-norm of shallow neural networks. First, despite its non-smoothness and non-convexity it allows a closed form proximal operator which can be efficiently computed, allowing the use of stochastic proxi ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2020

Pre-Impact Detection Algorithm to Identify Tripping Events Using Wearable Sensors

Silvestro Micera

This study aimed to investigate the performance of an updated version of our pre-impact detection algorithm parsing out the output of a set of Inertial Measurement Units (IMUs) placed on lower limbs and designed to recognize signs of lack of balance due to ...

2019

Neural-Network Optimized 1-bit Precoding for Massive MU-MIMO

Alexios Konstantinos Balatsoukas Stimming, Christoph Studer

Base station (BS) architectures for massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems are equipped with hundreds of antennas to serve tens of users on the same time-frequency channel. The immense number of BS antennas incurs hi ...

IEEE2019

Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs

Matthias Grossglauser, Negar Kiyavash

Graph alignment in two correlated random graphs refers to the task of identifying the correspondence between vertex sets of the graphs. Recent results have characterized the exact information-theoretic threshold for graph alignment in correlated Erdös-Rény ...

Association for Computing Machinery (ACM)2019