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Generalized connection graph method for synchronization in asymmetrical networks

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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

How to learn a graph from smooth signals

Vasilis Kalofolias

We propose a framework that learns the graph structure underlying a set of smooth signals. Given a real m by n matrix X whose rows reside on the vertices of an unknown graph, we learn the edge weights w under the smoothness assumption that trace(X^TLX) is ...

2016

Diffusion social learning over weakly-connected graphs

Ali H. Sayed, Bicheng Ying

In this paper, we study diffusion social learning over weakly-connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some circumstances that we clarif ...

IEEE2016

Information Exchange and Learning Dynamics Over Weakly Connected Adaptive Networks

Ali H. Sayed, Bicheng Ying

This paper examines the learning mechanism of adaptive agents over weakly connected graphs and reveals an interesting behavior on how information flows through such topologies. The results clarify how asymmetries in the exchange of data can mask local info ...

IEEE2016

Chaos: Scale-out Graph Processing from Secondary Storage

Willy Zwaenepoel, Laurent Bindschaedler, Amitabha Roy, Jasmina Malicevic

Chaos scales graph processing from secondary storage to multiple machines in a cluster. Earlier systems that process graphs from secondary storage are restricted to a single ma- chine, and therefore limited by the bandwidth and capacity of the storage syst ...

2015

From Compact Semi-Toric Systems To Hamiltonian S-1-Spaces

Silvia Sabatini

We show how any labeled convex polygon associated to a compact semi-toric system, as de fined by V (u) over tilde Ngoc, determines Karshon's labeled directed graph which classifies the underlying Hamiltonian S-1-space up to isomorphism. Then we characteriz ...

Amer Inst Mathematical Sciences2015

Scale-up Graph Processing in the Cloud: Challenges and Solutions

Willy Zwaenepoel, Amitabha Roy, Jasmina Malicevic

Processing large graphs is an important part of the big-data problem. Recently a number of scale-up systems such as X-Stream, Graphchi and Turbograph have been proposed for processing large graphs using secondary storage on a single machine. The design and ...

Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

Relationships between entities in datasets are often of multiple nature, like geographical distance, social relationships, or common interests among people in a social network, for example. This information can naturally be modeled by a set of weighted and ...

Institute of Electrical and Electronics Engineers2014

Reversible Sesqui-Pushout Rewriting, Graph Transformation

Sandro Stucki

The paper proposes a variant of sesqui-pushout rewriting (SqPO) that allows one to develop the theory of nested application conditions (NACs) for arbitrary rule spans; this is a considerable generalisation compared with existing results for NACs, which onl ...

Springer2014

Privacy and Dynamics of Social Networks

Pedram Pedarsani

Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...

EPFL2013