Publications associées à Suite généralisée

Spatiotemporal energy‐density distribution of time‐reversed electromagnetic fields

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami, Elias Per Joachim Le Boudec, Nicolas Mora Parra

Time reversal exploits the invariance of electromagnetic wave propagation in reciprocal and lossless media to localize radiating sources. Time-reversed measurements are back-propagated in a simulated domain and converge to the unknown source location. The ...

2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Conditional gradient methods for stochastically constrained convex minimization

Volkan Cevher, Ya-Ping Hsieh, Ahmet Alacaoglu, Maria-Luiza Vladarean

We propose two novel conditional gradient-based methods for solving structured stochastic convex optimization problems with a large number of linear constraints. Instances of this template naturally arise from SDP-relaxations of combinatorial problems, whi ...

2020

Scale-Adaptive Superpixels

Pascal Fua, Sabine Süsstrunk, Radhakrishna Achanta, Pablo Marquez Neila

Size uniformity is one of the prominent features of superpixels. However, size uniformity rarely conforms to the varying content of an image. The chosen size of the superpixels therefore represents a compromise - how to obtain the fewest superpixels withou ...

Society for Imaging Science and Technology2018

Sequences with Minimal Time-Frequency Uncertainty

Martin Vetterli, Reza Parhizkar, Yann Barbotin

A central problem in signal processing and communications is to design signals that are compact both in time and frequency. Heisenberg's uncertainty principle states that a given function cannot be arbitrarily compact both in time and frequency, defining a ...

Elsevier2015

Sequences with Minimal Time-Frequency Spreads

Martin Vetterli, Reza Parhizkar, Yann Barbotin

For a given time or frequency spread, one can always find continuous- time signals, which achieve the Heisenberg uncertainty principle bound. This is known, however, not to be the case for discrete-time sequences; only widely spread sequences asymptoticall ...

Ieee2013

Euclidean Distance Matrices : Properties, Algorithms and Applications

Reza Parhizkar

Euclidean distance matrices (EDMs) are central players in many diverse fields including psychometrics, NMR spectroscopy, machine learning and sensor networks. However, they are not often exploited in signal processing. In this thesis, we analyze attributes ...

EPFL2013

Routes to Novel Colloidal Gels

Francesco Varrato

The thesis describes how demixing of binary colloidal mixtures could be used to design new kinds of amorphous structures. We show that a rich phase behavior emerges, dependent on density (colloidal concentration) and composition (species relative populatio ...

EPFL2012

Reprint of: Weak epsilon-nets have basis of size O(1/epsilonlog(1/epsilon)) in any dimension

Given a set P of n points in R-d and epsilon > 0, we consider the problem of constructing weak E-nets for P. We show the following: pick a random sample Q of size O(1/epsilon log(1/epsilon)) from P. Then, with constant probability, a weak epsilon-net of P ...

2010

Multiple source multiple destination topology inference using network coding

Christina Fragouli

In this paper, we combine network coding and tomographic techniques for topology inference. Our goal is to infer the topology of a network by sending probes between a given set of multiple sources and multiple receivers and by having intermediate nodes per ...

2009