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System, device, and method for contextual knowledge retrieval and display

Publications associées (68)

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Graph learning under sparsity priors

Pascal Frossard, Hermina Petric Maretic

Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. ...

Ieee2017

Graph-based Methods for Visualization and Clustering

Johann Paratte

The amount of data that we produce and consume is larger than it has been at any point in the history of mankind, and it keeps growing exponentially. All this information, gathered in overwhelming volumes, often comes with two problematic characteristics: ...

EPFL2017

Compressive Embedding and Visualization using Graphs

Pierre Vandergheynst, Nathanaël Perraudin, Johann Paratte

Visualizing high-dimensional data has been a focus in data analysis communities for decades, which has led to the design of many algorithms, some of which are now considered references (such as t-SNE for example). In our era of overwhelming data volumes, t ...

arXiv e-print archive2017

TimeRank: A dynamic approach to rate scholars using citations

Giovanni Colavizza, Massimo Franceschet

Rating has become a common practice of modern science. No rating system can be considered as final, but instead several approaches can be taken, which magnify different aspects of the fabric of science. We introduce an approach for rating scholars which us ...

Elsevier Science Bv2017

Learning Laplacian Matrix in Smooth Graph Signal Representations

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful graph is not alwa ...

Institute of Electrical and Electronics Engineers2016

Assembling a Network out of Ambiguous Patches

Matthias Grossglauser, Lyudmila Yartseva, Jefferson Elbert Simões

Many graph mining and network analysis problems rely on the availability of the full network over a set of nodes. But inferring a full network is sometimes non-trivial if the raw data is in the form of many small {\em patches} or subgraphs, of the true net ...

2016

Where You Are is Who You Are: User Identification by Matching Statistics

Martin Vetterli, Patrick Thiran, Jayakrishnan Unnikrishnan, Farid Movahedi Naini

Most users of online services have unique behavioral or usage patterns. These behavioral patterns can be used to identify and track users by using only the observed patterns in the behavior. We study the task of identifying users from statistics of their b ...

Institute of Electrical and Electronics Engineers2016

Automating Live Update for Generic Server Programs

Calin Iorgulescu

The pressing demand to deploy software updates without stopping running programs has fostered much research on live update systems in the past decades. Prior solutions, however, either make strong assumptions on the nature of the update or require extensiv ...

Ieee Computer Soc2016

Correcting for endogeneity using the EMIS method: a case study with revealed preference data

Michel Bierlaire, Anna Fernández Antolín

Endogeneity is an important issue that often arises in discrete choice models leading to biased estimates of the parameters. We propose the extended multiple indicator solution (EMIS) methodology to correct for it and exemplify it with a case study using r ...

2015

Mining, Modeling and Predicting Mobility

Mohamed Kafsi

Mobility is a central aspect of our life, and our movements reveal much more about us than simply our whereabouts. In this thesis, we are interested in mobility and study it from three different perspectives: the modeling perspective, the information-theor ...

EPFL2015