Publications related to OptiMoS: Optimal Sensing for Mobile Sensors

Fast Mean Estimation with Sub-Gaussian Rates

We present an improved analysis of the Euler-Maruyama discretization of the Langevin diffusion. Our analysis does not require global contractivity, and yields polynomial dependence on the time horizon. Compared to existing approaches, we make an additional ...

2019

Sampling at unknown locations, with an application in surface retrieval

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

We consider the problem of sampling at unknown locations. We prove that, in this setting, if we take arbitrarily many samples of a polynomial or real bandlimited signal, it is possible to find another function in the same class, arbitrarily far away from t ...

2017

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Model-based Rendezvous Calibration of Mobile Sensor Networks for Monitoring Air Quality

Alcherio Martinoli, Ali Marjovi, Adrian Arfire

Mobile Wireless Sensor Networks (WSNs) hold the potential to constitute a real game changer for our understanding of urban air pollution, through a significant augmentation of spatial resolution in measurement. However, temporal drift, crosssensitivity and ...

2015

Metropolis-Hastings sampling of paths

Michel Bierlaire, Gunnar Flötteröd

We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and he ...

2013

Linear Bayesian Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis

This paper proposes a simple linear Bayesian approach to reinforcement learning. We show that with an appropriate basis, a Bayesian linear Gaussian model is sufficient for accurately estimating the system dynamics, and in particular when we allow for corre ...

2013

On Sampling and Coding for Distributed Acoustic Sensing

Martin Vetterli, Emre Telatar, Robert Konsbruck

The issue of how to efficiently represent the data collected by a network of microphones recording spatio-temporal acoustic wave fields is addressed. Each sensor node in the network samples the sound field, quantizes the samples and transmits the encoded s ...

2012

Liquid-Quench Sampling System for the Analysis of Gas Streams from Biomass Gasification Processes. Part 1: Sampling Noncondensable Compounds

Christian Ludwig, Tilman J. Schildhauer

In biomass gasification plants and related research units, on-line analysis of noncondensable compounds (H-2, CO, CO2, CH4, and light hydrocarbons) and condensable compounds (water, tars, etc.) is desired. Long-duration on-line measurements are often a cha ...

Amer Chemical Soc2012

OptiMoS: Optimal Sensing for Mobile Sensors

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Fast Mean Estimation with Sub-Gaussian Rates

Sampling at unknown locations, with an application in surface retrieval

Shapes from Pixels

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Random sampling of bandlimited signals on graphs

Model-based Rendezvous Calibration of Mobile Sensor Networks for Monitoring Air Quality

Metropolis-Hastings sampling of paths

Linear Bayesian Reinforcement Learning

On Sampling and Coding for Distributed Acoustic Sensing

Liquid-Quench Sampling System for the Analysis of Gas Streams from Biomass Gasification Processes. Part 1: Sampling Noncondensable Compounds

Sampling at unknown locations, with an application in surface retrieval

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Fast Mean Estimation with Sub-Gaussian Rates

Shapes from Pixels

Random sampling of bandlimited signals on graphs

Metropolis-Hastings sampling of paths

Liquid-Quench Sampling System for the Analysis of Gas Streams from Biomass Gasification Processes. Part 1: Sampling Noncondensable Compounds

On Sampling and Coding for Distributed Acoustic Sensing

Model-based Rendezvous Calibration of Mobile Sensor Networks for Monitoring Air Quality

Linear Bayesian Reinforcement Learning