Publications related to Laplacian matrix

From data to structures

Weighted undirected graphs are a simple, yet powerful way to encode structure in data. A first question we need to address regarding such graphs is how to use them effectively to enhance machine learning problems. A second but more important question is ho ...

EPFL2016

Learning Laplacian Matrix in Smooth Graph Signal Representations

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful graph is not alwa ...

Institute of Electrical and Electronics Engineers2016

Voltage stabilization in DC microgrids: an approach based on line-independent plug-and-play controllers

Giancarlo Ferrari Trecate

We consider the problem of stabilizing voltages in DC microGrids (mGs) given by the interconnection of Distributed Generation Units (DGUs), power lines and loads. We propose a decentralized control architecture where the primary controller of each DGU can ...

2016

Constant Factor Approximation for ATSP with Two Edge Weights

Ola Nils Anders Svensson, Jakub Tarnawski

We give a constant factor approximation algorithm for the Asymmetric Traveling Salesman Problem on shortest path metrics of directed graphs with two different edge weights. For the case of unit edge weights, the first constant factor approximation was give ...

Springer Int Publishing Ag2016

Voltage stabilization in DC microgrids through coupling-independent plug-and-play controllers

Giancarlo Ferrari Trecate

This paper addresses the problem of stabilizing voltages in DC microgrids given by the interconnection of Distributed Generation Units (DGUs), power lines and loads. As in (Tucci et al., 2016), we propose a decentralized control architecture where the cont ...

2016

Optimal acoustic rake receiver

Martin Vetterli, Ivan Dokmanic, Robin Scheibler

An acoustic processing method for M acoustic receivers comprising the steps of: Determining a beamforming weight vector with M weights for the M acoustic receivers based on at least one the steering vector of at least one real acoustic source, on steering ...

2016

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We build upon recent advances in graph signal processing to propose a faster spectral clustering algorithm. Indeed, classical spectral clustering is based on the computation of the first

k

eigenvectors of the similarity matrix' Laplacian, whose computati ...

Ieee2016

A Spectral Method for Generating Surrogate Graph Signals

Dimitri Nestor Alice Van De Ville, Elvira Pirondini, Martina Coscia, Anna Vybornova

The increasing availability of network data is leading to a growing interest in processing of signals on graphs. One notable tool for extending conventional signal-processing operations to networks is the graph Fourier transform that can be obtained as the ...

Institute of Electrical and Electronics Engineers2016

Laplacian Matrix Learning for Smooth Graph Signal Representation

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the emerging field of signal processing on graphs. In this paper, we address the problem of learning graph Laplacians, which is similar to learning graph topologies, such that the input data fo ...

2015

Distributed Graph-based Convoy Control for Networked Intelligent Vehicles

Alcherio Martinoli, Ali Marjovi, Milos Vasic, Joseph Chadi Benoit Lemaitre

This paper presents an approach for formation control of multi-lane vehicular convoys in highways. We extend a Laplacian graph-based, distributed control law such that networked intelligent vehicles can join or leave the formation dynamically without jeopa ...

IEEE2015

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From data to structures

Learning Laplacian Matrix in Smooth Graph Signal Representations

Voltage stabilization in DC microgrids: an approach based on line-independent plug-and-play controllers

Constant Factor Approximation for ATSP with Two Edge Weights

Voltage stabilization in DC microgrids through coupling-independent plug-and-play controllers

Optimal acoustic rake receiver

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

A Spectral Method for Generating Surrogate Graph Signals

Laplacian Matrix Learning for Smooth Graph Signal Representation

Distributed Graph-based Convoy Control for Networked Intelligent Vehicles

Constant Factor Approximation for ATSP with Two Edge Weights

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Learning Laplacian Matrix in Smooth Graph Signal Representations

From data to structures

Voltage stabilization in DC microgrids through coupling-independent plug-and-play controllers

Voltage stabilization in DC microgrids: an approach based on line-independent plug-and-play controllers

Optimal acoustic rake receiver

Distributed Graph-based Convoy Control for Networked Intelligent Vehicles

A Spectral Method for Generating Surrogate Graph Signals

Laplacian Matrix Learning for Smooth Graph Signal Representation