Concept

Petersen graph

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Execution Trace Graph of Dataflow Process Networks

Marco Mattavelli, Simone Casale Brunet

The paper introduces and specifies a formalism that provides complete representations of dataflow process network (DPN) program executions, by means of directed acyclic graphs. Such graphs, also known as execution trace graphs (ETG), are composed of nodes ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Finding Perfect Matchings in Bipartite Hypergraphs

Chidambaram Annamalai

Haxell's condition [14] is a natural hypergraph analog of Hall's condition, which is a well-known necessary and sufficient condition for a bipartite graph to admit a perfect matching. That is, when Haxell's condition holds it forces the existence of a perf ...

SPRINGER HEIDELBERG2018

Robust and Efficient Data Clustering with Signal Processing on Graphs

Lionel Jérémie Martin

Data is pervasive in today's world and has actually been for quite some time. With the increasing volume of data to process, there is a need for faster and at least as accurate techniques than what we already have. In particular, the last decade recorded t ...

EPFL2018

Geometric Graph Matching Using Monte Carlo Tree Search

Pascal Fua, Jan Kybic, Miguel Amável Dos Santos Pinheiro

We present an efficient matching method for generalized geometric graphs. Such graphs consist of vertices in space connected by curves and can represent many real world structures such as road networks in remote sensing, or vessel networks in medical imagi ...

Ieee Computer Soc2017

Method and System for Fault Detection and Faulted Line Identification in Power Systems using Synchrophasors-Based Real-Time State Estimation

Mario Paolone, Paolo Romano, Marco Pignati, Lorenzo Zanni

A method for a faulted line identification in a power network, including, at a generic time-instant, solving a plurality of parallel phasor measurement units based real-time state estimators, the state estimators having among each other different and augme ...

2017

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

Exploring Selection Bias by Causal Frailty Models

Mats Julius Stensrud

Counter-intuitive associations appear frequently in epidemiology, and these results are often debated. In particular, several scenarios are characterized by a general risk factor that appears protective in particular subpopulations, for example, individual ...

2017

Stationary signal processing on graphs

Pierre Vandergheynst, Nathanaël Perraudin

Graphs are a central tool in machine learning and information processing as they allow to conveniently capture the structure of complex datasets. In this context, it is of high importance to develop flexible models of signals defined over graphs or network ...

Institute of Electrical and Electronics Engineers2017

Graph-Based Classification of Omnidirectional Images

Pascal Frossard, Renata Khasanova

Omnidirectional cameras are widely used in such areas as robotics and virtual reality as they provide a wide field of view. Their images are often processed with classical methods, which might unfortunately lead to non-optimal solutions as these methods ar ...

2017

Alignment and Assembly

Lyudmila Yartseva

Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction n ...

EPFL2017