Publications related to Cluster-and-Conquer: When Randomness Meets Graph Locality

Actuator Placement for Optimizing Network Performance under Controllability Constraints

Maryam Kamgarpour, Tyler Summers, Baiwei Guo, Orcun Karaca

With the rising importance of large-scale network control, the problem of actuator placement has received increasing attention. Our goal in this paper is to find a set of actuators minimizing the metric that measures the average energy consumption of the c ...

IEEE2019

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

Fingerprinting Big Data: The Case of KNN Graph Construction

Rachid Guerraoui, Anne-Marie Kermarrec, Olivier Ruas

We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...

2019

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Slobodan Mitrovic

We study the problem of maximizing a monotone submodular function subject to a cardinality constraint

k

, with the added twist that a number of items

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2017

Alignment and Assembly

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Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction n ...

EPFL2017

Network Alignment: Theory, Algorithms, and Applications

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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

Sparse Group Covers and Greedy Tree Approximations

Volkan Cevher, Luca Baldassarre

We consider the problem of finding a K-sparse approximation of a signal, such that the support of the approximation is the union of sets from a given collection, a.k.a. group structure. This problem subsumes the one of finding K-sparse tree approximations. ...

2015

Projection onto the Manifold of Elongated Structures for Accurate Extraction

Pascal Fua, Vincent Lepetit, Amos Sironi

Detection of elongated structures in 2D images and 3D image stacks is a critical prerequisite in many applications and Machine Learning-based approaches have recently been shown to deliver superior performance. However, these methods essentially classify i ...

2015

Right-Protected Data Publishing with Provable Distance-Based Mining

Michail Vlachos, Nikolaos Freris

Protection of one's intellectual property is a topic with important technological and legal facets. We provide mechanisms for establishing the ownership of a dataset consisting of multiple objects. The algorithms also preserve important properties of the d ...

Ieee Computer Soc2014

Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods

Jan Sickmann Hesthaven, Benjamin Stamm

We propose two new and enhanced algorithms for greedy sampling of high- dimensional functions. While the techniques have a substantial degree of generality, we frame the discussion in the context of methods for empirical interpolation and the devel- opment ...

EDP Sciences2014

Cluster-and-Conquer: When Randomness Meets Graph Locality

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Actuator Placement for Optimizing Network Performance under Controllability Constraints

New Graph Algorithms via Polyhedral Techniques

Fingerprinting Big Data: The Case of KNN Graph Construction

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Alignment and Assembly

Network Alignment: Theory, Algorithms, and Applications

Sparse Group Covers and Greedy Tree Approximations

Projection onto the Manifold of Elongated Structures for Accurate Extraction

Right-Protected Data Publishing with Provable Distance-Based Mining

Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods

New Graph Algorithms via Polyhedral Techniques

Fingerprinting Big Data: The Case of KNN Graph Construction

Projection onto the Manifold of Elongated Structures for Accurate Extraction

Alignment and Assembly

Network Alignment: Theory, Algorithms, and Applications

Actuator Placement for Optimizing Network Performance under Controllability Constraints

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods

Right-Protected Data Publishing with Provable Distance-Based Mining

Sparse Group Covers and Greedy Tree Approximations