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Pierre Vandergheynst

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Publications associées (216)

Song Recommendation with Non-Negative Matrix Factorization and Graph Total Variation

Pierre Vandergheynst, Xavier Bresson, Kirell Maël Benzi, Vasilis Kalofolias

This work formulates a novel song recommender system as a matrix completion problem that benefits from collaborative filtering through Non-negative Matrix Factorization (NMF) and content-based filtering via total variation (TV) on graphs. The graphs encode ...

Ieee2016

Vertex-Frequency Analysis on Graphs

Pierre Vandergheynst, David Shuman, Benjamin Ricaud

One of the key challenges in the area of signal processing on graphs is to design dictionaries and transform methods to identify and exploit structure in signals on weighted graphs. To do so, we need to account for the intrinsic geometric structure of the ...

Academic Press Inc Elsevier Science2016

Spectrum-Adapted Tight Graph Wavelet and Vertex-Frequency Frames

Pierre Vandergheynst, David Shuman

We consider the problem of designing spectral graph filters for the construction of dictionaries of atoms that can be used to efficiently represent signals residing on weighted graphs. While the filters used in previous spectral graph wavelet constructions ...

Institute of Electrical and Electronics Engineers2015

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

Pierre Vandergheynst, Mahdad Hosseini Kamal

We present a novel approach to the reconstruction of depth from light field data. Our method uses dictionary representations and group sparsity constraints to derive a convex formulation. Although our solution results in an increase of the problem dimensio ...

Springer-Verlag2015

Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks

Pierre Vandergheynst, Michael Bronstein

In this paper, we propose a generalization of convolutional neural networks (CNN) to non-Euclidean domains for the analysis of deformable shapes. Our construction is based on localized frequency analysis (a generalization of the windowed Fourier transform ...

Wiley-Blackwell2015

Robust Principal Component Analysis on Graphs

Pierre Vandergheynst, Xavier Bresson, Vasilis Kalofolias, Nauman Shahid, Michael Bronstein

Principal Component Analysis (PCA) is the most widely used tool for linear dimensionality reduction and clustering. Still it is highly sensitive to outliers and does not scale well with respect to the number of data samples. Robust PCA solves the first iss ...

2015

Graph-based denoising for time-varying point clouds

Pierre Vandergheynst, Johann Paratte, Yann Mikaël Schoenenberger

Noisy 3D point clouds arise in many applications. They may be due to errors when creating a 3D model from images or simply to imprecise depth sensors. Point clouds can be given geometrical structure using graphs created from the similarity information betw ...

2015

Laplacian Matrix Learning for Smooth Graph Signal Representation

Pascal Frossard, Pierre Vandergheynst, Ntorina Thanou, 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

Mapping resting-state dynamics on spatio-temporal graphs: a combined functional and diffusion MRI approach

Jean-Philippe Thiran, Pierre Vandergheynst, Xavier Bresson, Patric Hagmann, Alessandra Griffa, Kirell Maël Benzi, Benjamin Ricaud

2015

Ultra-low-power ECG front-end design based on compressed sensing

Pierre Vandergheynst, Hossein Mamaghanian

Ultra-low-power design has been a challenging area for design of the sensor front-ends especially in the area of Wireless Body Sensor Nodes (WBSN), where a limited amount of power budget and hardware resources are available. Since introduction of Compresse ...

ACM/IEEE Press2015

On spin scale-discretised wavelets on the sphere for the analysis of CMB polarisation

Pierre Vandergheynst, Yves Wiaux, Jason Douglas McEwen, Jean-Luc Starck

Cambridge, Cambridge University Press2014

Robust Real-time Pedestrians Detection in Urban Environments with a Network of Low Resolution Cameras

Michel Bierlaire, Pierre Vandergheynst, Alexandre Massoud Alahi

Detecting that pedestrians are present in front of a vehicle is highly desirable to avoid dangerous traffic situations. A novel vision-based system is presented to automatically detect far-away pedestrians with low-resolution cameras mounted in vehicles gi ...

Elsevier2014

A Compressed Sensing Framework for Magnetic Resonance Fingerprinting

Pierre Vandergheynst, Yves Wiaux, Gilles Puy

Inspired by the recently proposed Magnetic Resonance Fingerprinting (MRF) technique we develop a principled compressed sensing framework for quantitative MRI. The three key components are: a random pulse excitation sequence following the MRF technique; a r ...

Siam Publications2014

Compressed Quantitative MRI: Bloch Response Recovery through iterated projection

Pierre Vandergheynst, Yves Wiaux, Gilles Puy

Inspired by the recently proposed Magnetic Resonance Fin- gerprinting technique, we develop a principled compressed sensing framework for quantitative MRI. The three key com- ponents are: a random pulse excitation sequence following the MRF technique; a ra ...

2014

From Bits to Images: Inversion of Local Binary Descriptors

Pierre Vandergheynst, Alexandre Massoud Alahi, Laurent Jacques, Emmanuel D'Angelo

Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom ...

Institute of Electrical and Electronics Engineers2014

Compact Low-Power Cortical Recording Architecture for Compressive Multichannel Data Acquisition

Alexandre Schmid, Pierre Vandergheynst, Mahdad Hosseini Kamal, Mahsa Shoaran

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sp ...

2014

Approximate Compressed Sensing: Ultra-Low Power Biosignal Processing via Aggressive Voltage Scaling on a Hybrid Memory Multi-core Processor

Pierre Vandergheynst, David Atienza Alonso, Luca Benini, Hossein Mamaghanian

Technology scaling enables the design of low cost biosignal processing chips suited for emerging wireless body-area sensing applications. Energy consumption severely limits such applications and memories are becoming the energy bottleneck to achieve ultra- ...

IEEE/ACM Press2014

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

Pierre Vandergheynst, Mahdad Hosseini Kamal

2014

System and method for media library navigation and recommendation

Pierre Vandergheynst, Alexandre Massoud Alahi, Kirell Maël Benzi

The invention relates to a system and method to optimize navigation and recommendation in a distributed network of media libraries. According to the invention, it is proposed a system and a method to assist the selection of media items comprising the steps ...

2014

Reverberant Audio Source Separation via Sparse and Low-Rank Modeling

Pierre Vandergheynst

The performance of audio source separation from underde- termined convolutive mixture assuming known mixing filters can be significantly improved by using an analysis sparse prior optimized by a reweighting l1 scheme and a wideband data- fidelity term, as ...

IEEE Institute of Electrical and Electronics Engineers2014

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