Publications associées à Matrice d'incidence

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online inference time consumption. To improve the quality of the solution and r ...

State Grid Electric Power Research Inst2024

Spectral Hypergraph Sparsifiers of Nearly Linear Size

Mikhail Kapralov, Jakab Tardos

Graph sparsification has been studied extensively over the past two decades, culminating in spectral sparsifiers of optimal size (up to constant factors). Spectral hypergraph sparsification is a natural analogue of this problem, for which optimal bounds on ...

IEEE COMPUTER SOC2022

Multilayer Graph Clustering With Optimized Node Embedding

Pascal Frossard, Mireille El Gheche

We are interested in multilayer graph clustering, which aims at dividing the graph nodes into categories or communities. To do so, we propose to learn a clustering-friendly embedding of the graph nodes by solving an optimization problem that involves a fid ...

IEEE2021

Towards Tight Bounds for Spectral Sparsification of Hypergraphs

Mikhail Kapralov, Jakab Tardos

Cut and spectral sparsification of graphs have numerous applications, including e.g. speeding up algorithms for cuts and Laplacian solvers. These powerful notions have recently been extended to hypergraphs, which are much richer and may offer new applicati ...

ASSOC COMPUTING MACHINERY2021

Online Distributed Learning Over Graphs With Multitask Graph-Filter Models

Ali H. Sayed, Roula Nassif

In this article, we are interested in adaptive and distributed estimation of graph filters from streaming data. We formulate this problem as a consensus estimation problem over graphs, which can be addressed with diffusion LMS strategies. Most popular grap ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

GOT: An Optimal Transport framework for Graph comparison

Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic, Giovanni Chierchia

We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph signals defined with respect to the graph topology. This allows us to derive an ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

A Preconditioned Graph Diffusion LMS for Adaptive Graph Signal Processing

Ali H. Sayed, Roula Nassif

Graph filters, defined as polynomial functions of a graph-shift operator (GSO), play a key role in signal processing over graphs. In this work, we are interested in the adaptive and distributed estimation of graph filter coefficients from streaming graph s ...

IEEE COMPUTER SOC2018

Extension complexity of stable set polytopes of bipartite graphs

Yuri Faenza, Manuel Francesco Aprile

The extension complexity xc(P) of a polytope P is the minimum number of facets of a polytope that affinely projects to P. Let G be a bipartite graph with n vertices, m edges, and no isolated vertices. Let STAB(G) be the convex hull of the stable sets of G. ...

Springer2017

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Matrice d'incidence

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

Dispatch-aware Optimal Planning of Active Distribution Networks including Energy Storage Systems

Spectral Hypergraph Sparsifiers of Nearly Linear Size

Multilayer Graph Clustering With Optimized Node Embedding

Towards Tight Bounds for Spectral Sparsification of Hypergraphs

Online Distributed Learning Over Graphs With Multitask Graph-Filter Models

Graph Laplacians for Rotation Equivariant Convolutional Neural Networks

GOT: An Optimal Transport framework for Graph comparison

A Preconditioned Graph Diffusion LMS for Adaptive Graph Signal Processing

Extension complexity of stable set polytopes of bipartite graphs

Graph Chatbot

Chattez avec Graph Search

A Preconditioned Graph Diffusion LMS for Adaptive Graph Signal Processing

Dispatch-aware Optimal Planning of Active Distribution Networks including Energy Storage Systems

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

GOT: An Optimal Transport framework for Graph comparison

Towards Tight Bounds for Spectral Sparsification of Hypergraphs

Online Distributed Learning Over Graphs With Multitask Graph-Filter Models

Multilayer Graph Clustering With Optimized Node Embedding

Spectral Hypergraph Sparsifiers of Nearly Linear Size

Graph Laplacians for Rotation Equivariant Convolutional Neural Networks

Extension complexity of stable set polytopes of bipartite graphs