Publications related to Graph Transformations preserving the stability number

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Distributed Diffusion Adaptation Over Graph Signals

Ali H. Sayed, Jie Chen, Roula Nassif

Most works on graph signal processing assume static graph signals, which is a limitation even in comparison to traditional DSP techniques where signals are modeled as sequences that evolve over time. For broader applicability, it is necessary to develop te ...

IEEE2018

Spectral MAB for Unknown Graph Processes

Pascal Frossard, Laura Toni

In this work, we study graph-based multi-arms bandit (MAB) problems aimed at optimizing actions on irregular and high-dimensional graphs. More formally, we consider a decision-maker that takes sequential actions over time and observes the experienced rewar ...

IEEE Computer Society2018

Learning time varying graphs

Pascal Frossard, Andreas Loukas, Vasilis Kalofolias

We consider the problem of inferring the hidden structure of high-dimensional dynamic systems from the perspective of graph learning. In particular, we aim at capturing the dynamic relationships between nodes by a sequence of graphs. Our approach is motiva ...

Ieee2017

Independence number of generalized Petersen graphs

Javad Ebrahimi Boroojeni

Determining the size of a maximum independent set of a graph G, denoted by alpha(G), is an NP-hard problem. Therefore many attempts are made to find upper and lower bounds, or exact values of alpha(G) for special classes of graphs. This paper is aimed towa ...

Charles Babbage Res Ctr2016

Scaling a Reliable Distributed System

Alexandre David Olivier Maurer

We consider the problem of reliably connecting an arbitrarily large set of computers (nodes) with communication channels. Reliability means here the ability, for any two nodes, to remain connected (i.e., their ability to communicate) with probability at le ...

LPD EPFL2016

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

Nathanaël Perraudin, Benjamin Ricaud, Francesco Grassi

Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph. So far, the research efforts have been focused on static graph signals. However numerous applications involve graph signals evolv ...

2016

Graph-based compression of dynamic 3D point cloud sequences

Pascal Frossard

This paper addresses the problem of compression of 3D point cloud sequences that are characterized by moving 3D positions and color attributes. As temporally successive point cloud frames are similar, motion estimation is key to effective compression of th ...

Institute of Electrical and Electronics Engineers2016

On vertices and facets of combinatorial 2-level polytopes

Yuri Faenza, Manuel Francesco Aprile, Alfonso Bolívar Cevallos Manzano

2-level polytopes naturally appear in several areas of mathematics, including combinatorial optimization, polyhedral combinatorics, communication complexity, and statistics. We investigate upper bounds on the product of the number of facets and the number ...

Springer2016

Graph Transformations preserving the stability number

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Chat with Graph Search

Methods and apparatuses for encoding and decoding digital images or video streams

Distributed Diffusion Adaptation Over Graph Signals

Spectral MAB for Unknown Graph Processes

Learning time varying graphs

Independence number of generalized Petersen graphs

Scaling a Reliable Distributed System

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

Graph-based compression of dynamic 3D point cloud sequences

On vertices and facets of combinatorial 2-level polytopes

Modeling and Controlling epidemics : a graph perspective

On vertices and facets of combinatorial 2-level polytopes

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

Spectral MAB for Unknown Graph Processes

Methods and apparatuses for encoding and decoding digital images or video streams

Graph-based compression of dynamic 3D point cloud sequences

Modeling and Controlling epidemics : a graph perspective

Distributed Diffusion Adaptation Over Graph Signals

Scaling a Reliable Distributed System

Independence number of generalized Petersen graphs

Learning time varying graphs