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The Sketching Complexity of Graph and Hypergraph Counting

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A Bayesian Method for Matching Two Similar Graphs without Seeds

Matthias Grossglauser, Pedram Pedarsani

Approximate graph matching (AGM) refers to the problem of mapping the vertices of two structurally similar graphs, which has applications in social networks, computer vision, chemistry, and biology. Given its computational cost, AGM has mostly been limited ...

2013

On the Performance of Percolation Graph Matching

Matthias Grossglauser, Lyudmila Yartseva

Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and in ...

ACM2013

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

Optimizing Mix-zone Coverage in Pervasive Wireless Networks

Jean-Pierre Hubaux, Murtuza Jadliwala, Igor Bilogrevic

Location privacy is a major concern in pervasive networks where static device identifiers enable malicious eavesdroppers to continuously track users and their movements. In order to prevent such identifier-based tracking, devices could coordinate regular i ...

2013

Graph-Based Information Processing

Amin Karbasi

We live in a world characterized by massive information transfer and real-time communication. The demand for efficient yet low-complexity algorithms is widespread across different fields, including machine learning, signal processing and communications. Mo ...

EPFL2012

Multi-Graph Sampling Of Online Communities Via Mean Hitting Time

We derive a framework for sampling online communities based on the mean hitting time of its members, considering that there are multiple graphs associated with the same vertex set V representing the social network. First, we formulate random walk models on ...

Ieee2012

Efficient graph planarization in sensor networks and local routing algorithm

Florian Huc

In this paper, we propose an efficient planarization algorithm and a routing algorithm dedicated to Unit Disk Graphs whose nodes are localized using the Virtual Raw Anchor Coordinate system (VRAC). Our first algorithm computes a planar 2-spanner under ligh ...

Ieee2012

k-Quasi-Planar Graphs

A topological graph is k-quasi-planar if it does not contain k pairwise crossing edges. A topological graph is simple if every pair of its edges intersect at most once (either at a vertex or at their intersection). In 1996, Pach, Shahrokhi. and Szegedy [16 ...

Springer-Verlag Berlin2012

A Regularization Framework for Mobile Social Network Analysis

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and functions defined on the vertex set of the graph. We propose a regularization ...

2011

Optimizing Mixing in Pervasive Networks: A Graph-Theoretic Perspective

Jean-Pierre Hubaux, Murtuza Jadliwala, Igor Bilogrevic

One major concern in pervasive wireless applications is location privacy, where malicious eavesdroppers, based on static device identifiers, can continuously track users. As a commonly adopted countermeasure to prevent such identifier-based tracking, devic ...

Springer2011