Publications associées à M-DPOP: Faithful distributed implementation of efficient social choice problems

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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

M-DPOP: Faithful distributed implementation of efficient social choice problems

Graph Chatbot

Chattez avec Graph Search

Human computation for data, information, and knowledge management

Approximation algorithms for geometric dispersion

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Quantization Design for Distributed Optimization

Privacy-Preserving Schema Reuse

Near-Optimally Teaching the Crowd to Classify

Protecting Circuits From Computationally Bounded And Noisy Leakage

Assessing Gaps and Needs for Integrating Building Performance Optimization Tools in Net Zero Energy Buildings Design

Interactive Function Computation

MPTCP Is Not Pareto-Optimal: Performance Issues and a Possible Solution

Approximation algorithms for geometric dispersion

Near-Optimally Teaching the Crowd to Classify

Assessing Gaps and Needs for Integrating Building Performance Optimization Tools in Net Zero Energy Buildings Design

Human computation for data, information, and knowledge management

Accelerated Spectral Clustering Using Graph Filtering of Random Signals

Quantization Design for Distributed Optimization

Protecting Circuits From Computationally Bounded And Noisy Leakage

Privacy-Preserving Schema Reuse

Interactive Function Computation

MPTCP Is Not Pareto-Optimal: Performance Issues and a Possible Solution