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Quantization for Distributed Processing and Learning of Structured Data

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Robust Duplicate Detection of 2D and 3D Objects

Touradj Ebrahimi, Jong Seok Lee, Lutz Goldmann, Ivan Ivanov, Péter Vajda

In this paper, we analyze our graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images so that an explici ...

2010

Order-Optimal Consensus Through Randomized Path Averaging

Martin Vetterli, Patrick Thiran, Florence Bénézit

Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust mes- sage-passing schemes for distributed information processing over networks. However, for many topologies that are realistic for wire- less ...

Institute of Electrical and Electronics Engineers2010

Polynomial Filtering for Fast Convergence in Distributed Consensus

Pascal Frossard, Effrosyni Kokiopoulou

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by distributed linear iter ...

2009

Product Multicommodity Flow in Wireless Networks

Olivier Lévêque

We provide a tight approximate characterization of the n-dimensional product multicommodity flow (PMF) region for a wireless network of n nodes. Separate characterizations in terms of the spectral properties of appropriate network graphs are obtained in bo ...

2008

Networks of Mixed Canonic-Dissipative Systems and Dynamic Hebbian Learning

Max-Olivier Hongler, Julio Rodriguez

We consider a collection {O_k}_{k=1}^N of interacting parametric mixed canonical-dissipative systems, (MCD). Each individual Ok, exhibits, in absence of interaction, a limit cycle L_k on which the orbit circulation is parameterized by w_k(t). The underlyin ...

Shaker Verlag2008

Variations of coloring problems related to scheduling and discrete tomography

Bernard Ries

The graph coloring problem is one of the most famous problems in graph theory and has a large range of applications. It consists in coloring the vertices of an undirected graph with a given number of colors such that two adjacent vertices get different col ...

EPFL2007

Dynamic hebbian learning in adaptive frequency oscillators

Auke Ijspeert, Jonas Buchli, Ludovic Righetti

Nonlinear oscillators are widely used in biology, physics and engineering for modeling and control. They are interesting because of their synchronization properties when coupled to other dynamical systems. In this paper, we propose a learning rule for osci ...

2006

Efficient Distributed Multiresolution Processing for Data Gathering in Sensor Networks

Razvan Cristescu, Jugoslava Acimovic

We consider large sensor networks where the cost of collecting data from the network nodes to the data gathering sink is critical.~We propose several algorithms that use limited local communication and distributed signal processing to make communication mo ...

2005

From error probability to information theoretic signal and image processing

Torsten Butz

The signal processing community is increasingly interested in using information theoretic concepts to build signal processing algorithms for a variety of applications. A general theory on how to apply the mathematical concepts of information theory to the ...

EPFL2003

Optimization of high order perceptrons

Neural networks are widely applied in research and industry. However, their broader application is hampered by various technical details. Among these details are several training parameters and the choice of the topology of the network. The subject of this ...

École Polytechnique Fédérale de Lausanne1997