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Publications associées (44)

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How close are the eigenvectors and eigenvalues of the sample and actual covariance matrices?

Andreas Loukas

How many samples are sufficient to guarantee that the eigenvectors and eigenvalues of the sample covariance matrix are close to those of the actual covariance matrix? For a wide family of distributions, including distributions with finite second moment and ...

2017

Distributionally Robust Control of Constrained Stochastic Systems

Daniel Kuhn

We investigate the control of constrained stochastic linear systems when faced with only limited information regarding the disturbance process, i.e. when only the first two moments of the disturbance distribution are known. We consider two types of distrib ...

Institute of Electrical and Electronics Engineers2016

Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics

Sylvain Calinon, Ajay Kumar Tanwani

Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...

2016

Forecasting Uncertainty in Electricity Demand

Tri Kurniawan Wijaya

Generalized Additive Models (GAM) are a widely popular class of regression models to forecast electricity demand, due to their high accuracy, flexibility and interpretability. However, the residuals of the fitted GAM are typically heteroscedastic and lepto ...

2015

Asynchronous Adaptation and Learning Over Networks—Part III: Comparison Analysis

Ali H. Sayed

In Part II of this paper, also in this issue, we carried out a detailed mean-square-error analysis of the performance of asynchronous adaptation and learning over networks under a fairly general model for asynchronous events including random topologies, ra ...

Institute of Electrical and Electronics Engineers2015

From averaging to acceleration, there is only a step-size

Nicolas Henri Bernard Flammarion

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that a ...

2015

Reference-Free Automated Magnetic Sensor Calibration for Angle Estimation in Smart Knee Prostheses

Kamiar Aminian, Julien David Rechenmann, Arash Arami

In this work, we present a method for automated calibration of an implanted anisotropic magnetoresistive (AMR) sensor for measuring the internal-external rotation (IE) in a prosthetic knee without using any reference measurement. The measurement system con ...

Institute of Electrical and Electronics Engineers2014

Using out-of-language data to improve an under-resourced speech recognizer

Hervé Bourlard, Petr Motlicek, Philip Neil Garner, David Imseng

Under-resourced speech recognizers may benefit from data in languages other than the target language. In this paper, we report how to boost the performance of an Afrikaans automatic speech recognition system by using already available Dutch data. We succes ...

2014

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We introduce a recursive algorithm for performing compressed sensing on streaming data. The approach consists of a) recursive encoding, where we sample the input stream via overlapping windowing and make use of the previous measurement in obtaining the nex ...

Submitted to IEEE Transactions on Information Theory2013

Expert Judgements in Risk Analysis: a Strategy to Overcome Uncertainities

Thierry Meyer, Amela Groso, David Nicolas Plüss

There is a need for a risk analysis technique specific for academic research laboratories. Since accurate accident data, normally required for quantitative risk analysis, are not available for this environment, expert judgements are often used to describe ...

2013