Publications related to Vector Network Coding

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2020

New Graph Algorithms via Polyhedral Techniques

Jakub Tarnawski

In this thesis we give new algorithms for two fundamental graph problems. We develop novel ways of using linear programming formulations, even exponential-sized ones, to extract structure from problem instances and to guide algorithms in making progress. S ...

EPFL2019

Efficient large-scale graph processing: optimisations for storage, performance and evolving graphs

Jasmina Malicevic

Graph processing systems are used in a wide variety of fields, ranging from biology to social networks. Algorithms to mine graphs incur many random accesses, and the sparse nature of the graphs of interest, exacerbates this. As DRAM sustains high bandwidt ...

EPFL2019

Graph Learning with Partial Observations: Role of Degree Concentration

Ali H. Sayed, Augusto José Rabelo Almeida Santos

In this work we consider the problem of learning an Erdos-Renyi graph over a diffusion network when: i) data from only a limited subset of nodes are available (partial observation); ii) and the inferential goal is to discover the graph of interconnections ...

IEEE2019

Local Approximation of the Maximum Cut in Regular Graphs

Etienne Michel François Bamas

This paper is devoted to the distributed complexity of finding an approximation of the maximum cut in graphs. A classical algorithm consists in letting each vertex choose its side of the cut uniformly at random. This does not require any communication and ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

On The Move: Localization With Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic, Puoya Tabaghi

In this paper, we propose kinetic Euclidean distance matrices (KEDMs) a new algebraic tool for localization of moving points from spatio temporal distance measurements. KEDMs are inspired by the well-known Euclidean distance matrices (EDM) which model stat ...

IEEE2019

When Stuck, Flip a Coin

Slobodan Mitrovic

Many modern services need to routinely perform tasks on a large scale. This prompts us to consider the following question: How can we design efficient algorithms for large-scale computation? In this thesis, we focus on devising a general strategy to addr ...

EPFL2018

Node-weighted network design and maximum sub-determinants

Carsten Moldenhauer

We consider the Node-weighted Steiner Forest problem on planar graphs. Demaine et al. showed that a generic primal-dual algorithm gives a 6-approximation. We present two different proofs of an approximation factor of~

3

. Then, we draw a connection to Goem ...

EPFL2014

EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation Algorithms from RGB and RGB-D Cameras

Jean-Marc Odobez, Florent Monay Michaud, Kenneth Alberto Funes Mora

The lack of a common benchmark for the evaluation of the gaze estimation task from RGB and RGB-D data is a serious limitation for distinguishing the advantages and disadvantages of the many proposed algorithms found in the literature. This paper intends to ...

ACM2014

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

Vector Network Coding

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Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

New Graph Algorithms via Polyhedral Techniques

Efficient large-scale graph processing: optimisations for storage, performance and evolving graphs

Graph Learning with Partial Observations: Role of Degree Concentration

Local Approximation of the Maximum Cut in Regular Graphs

On The Move: Localization With Kinetic Euclidean Distance Matrices

When Stuck, Flip a Coin

Node-weighted network design and maximum sub-determinants

EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation Algorithms from RGB and RGB-D Cameras

On the Performance of Percolation Graph Matching

New Graph Algorithms via Polyhedral Techniques

When Stuck, Flip a Coin

Local Approximation of the Maximum Cut in Regular Graphs

Efficient large-scale graph processing: optimisations for storage, performance and evolving graphs

Graph Learning with Partial Observations: Role of Degree Concentration

On The Move: Localization With Kinetic Euclidean Distance Matrices

Node-weighted network design and maximum sub-determinants

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

On the Performance of Percolation Graph Matching

EYEDIAP: A Database for the Development and Evaluation of Gaze Estimation Algorithms from RGB and RGB-D Cameras