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Some first results on the consistency of spatial regression with partial differential equation regularization

Publications associées (92)

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Calibration of optical tweezers with non-spherical probes via high-resolution detection of Brownian motion

László Forró, Richard Gaal, Flavio Maurizio Mor, Sylvia Jeney

Optical tweezers are commonly used and powerful tools to perform force measurements on the piconewton scale and to detect nanometer-scaled displacements. However, the precision of these instruments relies to a great extent on the accuracy of the calibratio ...

Elsevier Science Bv2015

An anisotropic adaptive finite element algorithm for transonic viscous flows around a wing

Marco Picasso, Wissam Hassan

An adaptive finite element algorithm to compute transonic viscous flows around a wing is presented. The adaptive criteria is based on an anisotropic error estimator in the 115 semi-norm, justified for an advection-diffusion problem with stabilized finite e ...

Pergamon-Elsevier Science Ltd2015

Multitask diffusion LMS with sparsity-based regularization

Ali H. Sayed, Roula Nassif

In this work, a diffusion-type algorithm is proposed to solve multitask estimation problems where each cluster of nodes is interested in estimating its own optimum parameter vector in a distributed manner. The approach relies on minimizing a global mean-sq ...

IEEE2015

Multitask Diffusion Adaptation Over Networks

Ali H. Sayed, Jie Chen

Adaptive networks are suitable for decentralized inference tasks. Recent works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are man ...

Institute of Electrical and Electronics Engineers2014

Time–Data Tradeoffs by Aggressive Smoothing

Volkan Cevher

This paper proposes a tradeoff between sample complexity and computation time that applies to statistical estimators based on convex optimization. As the amount of data increases, we can smooth optimization problems more and more aggressively to achieve ac ...

2014

Diffusion LMS for Clustered Multitask Networks

Ali H. Sayed

Recent research works on distributed adaptive networks have inten- sively studied the case where the nodes estimate a common parame- ter vector collaboratively. However, there are many applications that are multitask-oriented in the sense that there are mu ...

2014

Bayesian Estimation for Continuous-Time Sparse Stochastic Processes

Michaël Unser, Arash Amini, Emrah Bostan, Ulugbek Kamilov

We consider continuous-time sparse stochastic processes from which we have only a finite number of noisy/noiseless samples. Our goal is to estimate the noiseless samples (denoising) and the signal in-between (interpolation problem). By relying on tools fro ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

Michaël Unser, Emrah Bostan, Ulugbek Kamilov, Abbas Kazerouni

We introduce a new approach for the implementation of minimum mean-square error (MMSE) denoising for signals with decoupled derivatives. Our method casts the problem as a penalized least-squares regression in the redundant wavelet domain. It exploits the l ...

Ieee-Inst Electrical Electronics Engineers Inc2013

OFDM Channel Estimation Based on Impulse Response Decimation: Analysis and Novel Algorithms

Stefano Rosati

In this paper, OFDM data-aided channel estimation based on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSS) is addressed. Our aim is to approach the Minimum Mean Square Error (MMSE) channel es ...

Institute of Electrical and Electronics Engineers2012

Robust parameter estimation for the Ornstein-Uhlenbeck process

Sonja Rieder

In this paper, we derive elementary M- and optimally robust asymptotic linear (AL)-estimates for the parameters of an Ornstein-Uhlenbeck process. Simulation and estimation of the process are already well-studied, see Iacus (Simulation and inference for sto ...

Springer-Verlag2012