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Information Processing and Structure of Dynamical Networks

Publications associées (265)

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GDSP: A graphical perspective on the distributed storage systems

Michael Christoph Gastpar, Saeid Sahraei

The classical distributed storage problem can be modeled by a k-uniform complete hyper-graph where vertices represent servers and hyper-edges represent users. Hence each hyper-edge should be able to recover the full file using only the memories of the vert ...

2017

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

Large Scale Graph Learning from Smooth Signals

Nathanaël Perraudin, Vasilis Kalofolias

Graphs are a prevalent tool in data science, as they model the inherent structure of the data. They have been used successfully in unsupervised and semi-supervised learning. Typically they are constructed either by connecting nearest samples, or by learnin ...

2017

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 ...

2017

From data to structures

Vasilis Kalofolias

Weighted undirected graphs are a simple, yet powerful way to encode structure in data. A first question we need to address regarding such graphs is how to use them effectively to enhance machine learning problems. A second but more important question is ho ...

EPFL2016

Infectious Disease Containment Based on a Wireless Sensor System

Marcel Salathé, Xiao Sun

Infectious diseases pose a serious threat to public health due to its high infectivity and potentially high mortality. One of the most effective ways to protect people from being infected by these diseases is through vaccination. However, due to various re ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Network Alignment: Theory, Algorithms, and Applications

Ehsan Kazemi

Networks are central in the modeling and analysis of many large-scale human and technical systems, and they have applications in diverse fields such as computer science, biology, social sciences, and economics. Recently, network mining has been an active a ...

EPFL2016

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Pierre Vandergheynst, Xavier Bresson, Michaël Defferrard

In this work, we are interested in generalizing convolutional neural networks (CNNs) from low-dimensional regular grids, where image, video and speech are represented, to high-dimensional irregular domains, such as social networks, brain connectomes or wor ...

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

Performance limits of single-agent and multi-agent sub-gradient stochastic learning

Ali H. Sayed, Bicheng Ying

This work examines the performance of stochastic sub-gradient learning strategies, for both cases of stand-alone and networked agents, under weaker conditions than usually considered in the literature. It is shown that these conditions are automatically sa ...

IEEE2016