Publications associées à Reducing Randomness in Matrix Models for Wireless Communication

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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

Reducing Randomness in Matrix Models for Wireless Communication

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Chattez avec Graph Search

Fast recovery and approximation of hidden Cauchy structure

Soft optical composites for tunable transmittance

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

On Polynomial Lieb–Robinson Bounds for the XY Chain in a Decaying Random Field

MATHICSE Technical Report : Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

Incentive Schemes for Participatory Sensing

Lyapunov exponents of random walks in small random potential: the upper bound

Masking vs. Multiparty Computation: How Large Is the Gap for AES?

Towards a High-Speed Quantum Random Number Generator

Asynchronous diffusion adaptation over networks

Lyapunov exponents of random walks in small random potential: the upper bound

Towards a High-Speed Quantum Random Number Generator

Soft optical composites for tunable transmittance

MATHICSE Technical Report : Multi-index stochastic collocation convergence rates for random PDEs with parametric regularity

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Fast recovery and approximation of hidden Cauchy structure

Incentive Schemes for Participatory Sensing

On Polynomial Lieb–Robinson Bounds for the XY Chain in a Decaying Random Field

Masking vs. Multiparty Computation: How Large Is the Gap for AES?

Asynchronous diffusion adaptation over networks