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Optimized Quantization in Distributed Graph Signal Filtering

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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

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 ...

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

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

Privacy and Dynamics of Social Networks (PhD Thesis: pre-print)

Pedram Pedarsani

2012

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

Reduced-Dimension Linear Transform Coding of Correlated Signals in Networks

Michael Christoph Gastpar, Naveen Goela

A model called the linear transform network (LTN) is proposed to analyze the compression and estimation of correlated signals transmitted over directed acyclic graphs (DAGs). An LTN is a DAG network with multiple source and receiver nodes. Source nodes tra ...

Institute of Electrical and Electronics Engineers2012

Degraded two-message multicast over graphs

Christina Fragouli, Shirin Saeedi Bidokhti

We consider communication of two degraded mes- sage sets over graphs where a common source sends two prioritized messages (a common and a private message) to several receivers. All receivers require the common message and a subset of the receivers require ...

2011

Degraded two-message multicast over graphs

Christina Fragouli, Shirin Saeedi Bidokhti

In this work we consider a graph G where a common source sends two messages W1 and W2 to several receivers D1, D2, . . . , DK. The first two receivers D1 and D2 would like to receive message W1, while receivers D3, . . . , DK would like to receive both mes ...

2011

Information Processing and Structure of Dynamical Networks

Ali Ajdari Rad

Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...

EPFL2011