Publications associées à Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

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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

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

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Chattez avec Graph Search

Intearcting Brownian Swarms: Some Analytical Results

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

The Chaining Lemma and Its Application

Reconciling Factor Graph with User Feedback

Adaptive polynomial approximation by means of random discrete least squares

Stochastic frequency reserve provision by chance-constrained control of commercial buildings

Solvation quantities from a COSMO-RS equation of state

On the Continuity of Characteristic Functionals and Sparse Stochastic Modeling

A New Entropy Power Inequality for Integer-Valued Random Variables

Perturbation analysis for the Darcy problem with log-normal permeability

Adaptive polynomial approximation by means of random discrete least squares

The Chaining Lemma and Its Application

On the Continuity of Characteristic Functionals and Sparse Stochastic Modeling

Intearcting Brownian Swarms: Some Analytical Results

Stochastic frequency reserve provision by chance-constrained control of commercial buildings

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Perturbation analysis for the Darcy problem with log-normal permeability

Solvation quantities from a COSMO-RS equation of state

A New Entropy Power Inequality for Integer-Valued Random Variables

Reconciling Factor Graph with User Feedback