Pierre Vandergheynst

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Professor of Electrical Engineering, Swiss Federal Institute of Technology (EPFL), Vice President at Swiss Federal Institute of Technology Lausanne

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

In this work, we propose an automatic evaluation and comparison of the b...
02/17/2020 ∙ by Volodymyr Miz, et al. ∙ 0 ∙ share

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Some limitations of norm based generalization bounds in deep neural networks

Deep convolutional neural networks have been shown to be able to fit a l...
05/23/2019 ∙ by Konstantinos Pitas, et al. ∙ 5 ∙ share

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Revisiting hard thresholding for DNN pruning

The most common method for DNN pruning is hard thresholding of network w...
05/21/2019 ∙ by Konstantinos Pitas, et al. ∙ 4 ∙ share

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A Graph-structured Dataset for Wikipedia Research

Wikipedia is a rich and invaluable source of information. Its central pl...
03/20/2019 ∙ by Nicolas Aspert, et al. ∙ 0 ∙ share

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FeTa: A DCA Pruning Algorithm with Generalization Error Guarantees

Recent DNN pruning algorithms have succeeded in reducing the number of p...
03/12/2018 ∙ by Konstantinos Pitas, et al. ∙ 0 ∙ share

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Spectrally approximating large graphs with smaller graphs

How does coarsening affect the spectrum of a general graph? We provide c...
02/21/2018 ∙ by Andreas Loukas, et al. ∙ 0 ∙ share

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Joint Estimation of Room Geometry and Modes with Compressed Sensing

Acoustical behavior of a room for a given position of microphone and sou...
02/16/2018 ∙ by Helena Peic Tukuljac, et al. ∙ 0 ∙ share

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PAC-Bayesian Margin Bounds for Convolutional Neural Networks - Technical Report

Recently the generalisation error of deep neural networks has been analy...
12/30/2017 ∙ by Pitas Konstantinos, et al. ∙ 0 ∙ share

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Wikipedia graph mining: dynamic structure of collective memory

Wikipedia is the biggest encyclopedia ever created and the fifth most vi...
10/01/2017 ∙ by Volodymyr Miz, et al. ∙ 0 ∙ share

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Localization of Sound Sources in a Room with One Microphone

Estimation of the location of sound sources is usually done using microp...
07/14/2017 ∙ by Helena Peic Tukuljac, et al. ∙ 0 ∙ share

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Fast Approximate Spectral Clustering for Dynamic Networks

Spectral clustering is a widely studied problem, yet its complexity is p...
06/12/2017 ∙ by Lionel Martin, et al. ∙ 0 ∙ share

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Compressive Embedding and Visualization using Graphs

Visualizing high-dimensional data has been a focus in data analysis comm...
02/19/2017 ∙ by Johan Paratte, et al. ∙ 0 ∙ share

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Structured Sequence Modeling with Graph Convolutional Recurrent Networks

This paper introduces Graph Convolutional Recurrent Network (GCRN), a de...
12/22/2016 ∙ by Youngjoo Seo, et al. ∙ 0 ∙ share

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Geometric deep learning: going beyond Euclidean data

Many scientific fields study data with an underlying structure that is a...
11/24/2016 ∙ by Michael M. Bronstein, et al. ∙ 0 ∙ share

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Multilinear Low-Rank Tensors on Graphs & Applications

We propose a new framework for the analysis of low-rank tensors which li...
11/15/2016 ∙ by Nauman Shahid, et al. ∙ 0 ∙ share

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Adaptive Graph-based Total Variation for Tomographic Reconstructions

Sparsity exploiting image reconstruction (SER) methods have been extensi...
10/04/2016 ∙ by Faisal, et al. ∙ 0 ∙ share

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Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

In this work, we are interested in generalizing convolutional neural net...
06/30/2016 ∙ by Michaël Defferrard, et al. ∙ 0 ∙ share

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Towards stationary time-vertex signal processing

Graph-based methods for signal processing have shown promise for the ana...
06/22/2016 ∙ by Nathanaël Perraudin, et al. ∙ 0 ∙ share

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Graph Based Sinogram Denoising for Tomographic Reconstructions

Limited data and low dose constraints are common problems in a variety o...
03/14/2016 ∙ by Faisal, et al. ∙ 0 ∙ share

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Global and Local Uncertainty Principles for Signals on Graphs

Uncertainty principles such as Heisenberg's provide limits on the time-f...
03/10/2016 ∙ by Nathanaël Perraudin, et al. ∙ 0 ∙ share

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Compressive Spectral Clustering

Spectral clustering has become a popular technique due to its high perfo...
02/05/2016 ∙ by Nicolas Tremblay, et al. ∙ 0 ∙ share

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Stationary signal processing on graphs

Graphs are a central tool in machine learning and information processing...
01/11/2016 ∙ by Nathanaël Perraudin, et al. ∙ 0 ∙ share

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

This work formulates a novel song recommender system as a matrix complet...
01/08/2016 ∙ by Kirell Benzi, et al. ∙ 0 ∙ share

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Random sampling of bandlimited signals on graphs

We study the problem of sampling k-bandlimited signals on graphs. We pro...
11/16/2015 ∙ by Gilles Puy, et al. ∙ 0 ∙ share

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Graph-based denoising for time-varying point clouds

Noisy 3D point clouds arise in many applications. They may be due to err...
11/16/2015 ∙ by Yann Schoenenberger, et al. ∙ 0 ∙ share

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Fast Robust PCA on Graphs

Mining useful clusters from high dimensional data has received significa...
07/29/2015 ∙ by Nauman Shahid, et al. ∙ 0 ∙ share

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Robust Principal Component Analysis on Graphs

Principal Component Analysis (PCA) is the most widely used tool for line...
04/23/2015 ∙ by Nauman Shahid, et al. ∙ 0 ∙ share

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Geodesic convolutional neural networks on Riemannian manifolds

Feature descriptors play a crucial role in a wide range of geometry anal...
01/26/2015 ∙ by Jonathan Masci, et al. ∙ 0 ∙ share

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Functional correspondence by matrix completion

In this paper, we consider the problem of finding dense intrinsic corres...
12/27/2014 ∙ by Artiom Kovnatsky, et al. ∙ 0 ∙ share

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Matrix Completion on Graphs

The problem of finding the missing values of a matrix given a few of its...
08/07/2014 ∙ by Vassilis Kalofolias, et al. ∙ 0 ∙ share

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Learning Laplacian Matrix in Smooth Graph Signal Representations

The construction of a meaningful graph plays a crucial role in the succe...
06/30/2014 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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UNLocBoX: A MATLAB convex optimization toolbox for proximal-splitting methods

Convex optimization is an essential tool for machine learning, as many o...
02/04/2014 ∙ by Nathanaël Perraudin, et al. ∙ 0 ∙ share

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Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds

Relationships between entities in datasets are often of multiple nature,...
03/09/2013 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Robust image reconstruction from multi-view measurements

We propose a novel method to accurately reconstruct a set of images repr...
12/13/2012 ∙ by Gilles Puy, et al. ∙ 0 ∙ share

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From Bits to Images: Inversion of Local Binary Descriptors

Local Binary Descriptors are becoming more and more popular for image ma...
11/06/2012 ∙ by Emmanuel d'Angelo, et al. ∙ 0 ∙ share

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Clustering with Multi-Layer Graphs: A Spectral Perspective

Observational data usually comes with a multimodal nature, which means t...
06/11/2011 ∙ by Xiaowen Dong, et al. ∙ 0 ∙ share

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Classification via Incoherent Subspaces

This article presents a new classification framework that can extract in...
05/10/2010 ∙ by Karin Schnass, et al. ∙ 0 ∙ share

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Pierre Vandergheynst

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