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Privacy and Dynamics of Social Networks

Publications associées (225)

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Multi-Graph Regularization For Efficient Delivery Of User Generated Content In Online Social Networks

We present a methodology for enhancing the delivery of user-generated content in online social networks. To this end, we first regularize the social graph via node capacity and link cost information associated with the underlying data network. We then desi ...

2011

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

Leveraging User-Generated Content for Information Discovery on the Web

Adriana Budura

The large-scale adoption of the Web 2.0 paradigm has revolutionized the way we interact with the Web today. End-users, so far mainly passive consumers of information are now becoming active information producers, creating, uploading, and commenting on all ...

EPFL2010

Estimating small-world topology of neural networks from multi-electrode recordings

Wulfram Gerstner, Joao Emanuel Felipe Gerhard

Since the seminal work of Watts in the late 90s [1], graph-theoretic analyses have been performed on many complex dynamic networks, including brain structures [2]. Most studies have focused on functional connectivity defined between whole brain regions, us ...

2010

Automatic skill acquisition in Reinforcement Learning using connection graph stability centrality

Martin Hasler, Ali Ajdari Rad

Reinforcement Learning (RL) is an approach for training agent's behavior through trial-and-error interactions with a dynamic environment. An important problem of RL is that in large domains an enormous number of decisions are to be made. Hence, instead of ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Collaborative routing in mobile partitioned networks

Natasa Sarafijanovic-Djukic

Embedded wireless networks find a broad spectrum of applications in transportation, environmental monitoring, logistics, supply chain management, and "pocketswitched" communication. The node mobility patterns in these applications tend to give rise to spat ...

EPFL2010

Vector Network Coding

Christina Fragouli, Javad Ebrahimi Boroojeni

We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying th ...

2010

Vector Network Coding Algorithms

Christina Fragouli, Javad Ebrahimi Boroojeni

2010

Context-adaptive information flow allocation and media delivery in online social networks

Pascal Frossard

This paper investigates context-driven flow allocation and media delivery in online social networks. We exploit information on contacts and content preferences found in social networking applications to provide efficient network services and operation at t ...

2010